diff --git a/HISTORY.md b/HISTORY.md
index 586c8a4e..2f49bc6a 100644
--- a/HISTORY.md
+++ b/HISTORY.md
@@ -1,6 +1,20 @@
History
=======
+## 0.5.0 - 2023-05-23
+
+This version uses ``ml-stars`` package instead of ``mlprimitives``.
+
+### Issues resolved
+
+* Migrate to ml-stars – [Issue #418](https://github.com/signals-dev/Orion/issues/418) by @sarahmish
+* Updating ``best_cost`` in ``find_anomalies`` primitive – [Issue #403](https://github.com/signals-dev/Orion/issues/403) by @sarahmish
+* Retire ``lstm_dynamic_threshold_gpu`` and ``lstm_autoencoder_gpu`` pipeline maintenance – [Issue #373](https://github.com/signals-dev/Orion/issues/373) by @sarahmish
+* Typo in xlsxwriter dependency specification – [Issue #394](https://github.com/signals-dev/Orion/issues/394) by @sarahmish
+* ``orion.evaluate`` uses fails when fitting – [Issue #384](https://github.com/signals-dev/Orion/issues/384) by @sarahmish
+* AER pipeline with visualization option – [Issue #379](https://github.com/signals-dev/Orion/issues/379) by @sarahmish
+
+
## 0.4.1 - 2023-01-31
### Issues resolved
@@ -10,6 +24,7 @@ History
* Pin ``scikit-learn`` – [Issue #367](https://github.com/signals-dev/Orion/issues/367) by @sarahmish
* Fix VAE documentation – [Issue #360](https://github.com/signals-dev/Orion/issues/360) by @sarahmish
+
## 0.4.0 - 2022-11-08
This version introduces several new enhancements:
diff --git a/README.md b/README.md
index fabfd67d..63f332de 100644
--- a/README.md
+++ b/README.md
@@ -18,14 +18,13 @@
A machine learning library for unsupervised time series anomaly detection.
-| Important Links | |
-| ----------------------------------- | -------------------------------------------------------------------- |
-| :computer: **[Website]** | Check out the Sintel Website for more information about the project. |
-| :book: **[Documentation]** | Quickstarts, User and Development Guides, and API Reference. |
-| :star: **[Tutorials]** | Checkout our notebooks |
-| :octocat: **[Repository]** | The link to the Github Repository of this library. |
-| :scroll: **[License]** | The repository is published under the MIT License. |
-| :keyboard: **[Development Status]** | This software is in its Pre-Alpha stage. |
+| Important Links | |
+| --------------------------------------------- | -------------------------------------------------------------------- |
+| :computer: **[Website]** | Check out the Sintel Website for more information about the project. |
+| :book: **[Documentation]** | Quickstarts, User and Development Guides, and API Reference. |
+| :star: **[Tutorials]** | Checkout our notebooks |
+| :octocat: **[Repository]** | The link to the Github Repository of this library. |
+| :scroll: **[License]** | The repository is published under the MIT License. |
| [![][Slack Logo] **Community**][Community] | Join our Slack Workspace for announcements and discussions. |
[Website]: https://sintel.dev/
@@ -33,7 +32,6 @@ A machine learning library for unsupervised time series anomaly detection.
[Tutorials]: https://github.com/sintel-dev/Orion/tree/master/tutorials
[Repository]: https://github.com/sintel-dev/Orion
[License]: https://github.com/sintel-dev/Orion/blob/master/LICENSE
-[Development Status]: https://pypi.org/search/?c=Development+Status+%3A%3A+2+-+Pre-Alpha
[Community]: https://join.slack.com/t/sintel-space/shared_invite/zt-q147oimb-4HcphcxPfDAM0O9_4PaUtw
[Slack Logo]: https://github.com/sintel-dev/Orion/blob/master/docs/images/slack.png
@@ -87,20 +85,20 @@ which should show a signal with `timestamp` and `value`.
4 1222905600 -0.370746
```
-In this example we use `lstm_dynamic_threshold` pipeline and set some hyperparameters (in this case training epochs as 5).
+In this example we use `aer` pipeline and set some hyperparameters (in this case training epochs as 5).
```python3
from orion import Orion
hyperparameters = {
- 'keras.Sequential.LSTMTimeSeriesRegressor#1': {
+ 'orion.primitives.aer.AER#1': {
'epochs': 5,
'verbose': True
}
}
orion = Orion(
- pipeline='lstm_dynamic_threshold',
+ pipeline='aer',
hyperparameters=hyperparameters
)
@@ -120,7 +118,7 @@ The output of the previous command will be a ``pandas.DataFrame`` containing a t
```
start end severity
-0 1394323200 1399701600 0.673494
+0 1402012800 1403870400 0.122539
```
# Leaderboard
@@ -132,11 +130,12 @@ We run the benchmark on **11** datasets with their known grounth truth. We recor
|---------------------------|--------------------|
| AER | 10 |
| TadGAN | 7 |
-| LSTM Dynamic Thresholding | 8 |
+| LSTM Dynamic Thresholding | 7 |
| LSTM Autoencoder | 6 |
| Dense Autoencoder | 6 |
| VAE | 6 |
-| Azure | 0 |
+| [GANF](https://arxiv.org/pdf/2202.07857.pdf) | 6 |
+| [Azure](https://azure.microsoft.com/en-us/products/cognitive-services/anomaly-detector/) | 0 |
You can find the scores of each pipeline on every signal recorded in the [details Google Sheets document](https://docs.google.com/spreadsheets/d/1HaYDjY-BEXEObbi65fwG0om5d8kbRarhpK4mvOZVmqU/edit?usp=sharing). The summarized results can also be browsed in the following [summary Google Sheets document](https://docs.google.com/spreadsheets/d/1ZPUwYH8LhDovVeuJhKYGXYny7472HXVCzhX6D6PObmg/edit?usp=sharing).
@@ -150,24 +149,22 @@ Additional resources that might be of interest:
# Citation
-If you use **Orion** which is part of the **Sintel** ecosystem for your research, please consider citing the following paper:
+If you use **AER** for your research, please consider citing the following paper:
+
+Lawrence Wong, Dongyu Liu, Laure Berti-Equille, Sarah Alnegheimish, Kalyan Veeramachaneni. [AER: Auto-Encoder with Regression for Time Series Anomaly Detection](https://arxiv.org/pdf/2212.13558.pdf).
-Sarah Alnegheimish, Dongyu Liu, Carles Sala, Laure Berti-Equille, Kalyan Veeramachaneni. [Sintel: A Machine Learning Framework to Extract Insights from Signals](https://dl.acm.org/doi/pdf/10.1145/3514221.3517910).
```
-@inproceedings{alnegheimish2022sintel,
- title={Sintel: A Machine Learning Framework to Extract Insights from Signals},
- author={Alnegheimish, Sarah and Liu, Dongyu and Sala, Carles and Berti-Equille, Laure and Veeramachaneni, Kalyan},
- booktitle={Proceedings of the 2022 International Conference on Management of Data},
- pages = {1855–1865},
- numpages = {11},
- publisher={Association for Computing Machinery},
- doi = {10.1145/3514221.3517910},
- series = {SIGMOD '22},
+@inproceedings{wong2022aer,
+ title={AER: Auto-Encoder with Regression for Time Series Anomaly Detection},
+ author={Wong, Lawrence and Liu, Dongyu and Berti-Equille, Laure and Alnegheimish, Sarah and Veeramachaneni, Kalyan},
+ booktitle={2022 IEEE International Conference on Big Data (IEEE BigData)},
+ pages={1152-1161},
+ doi={10.1109/BigData55660.2022.10020857},
+ organization={IEEE},
year={2022}
}
```
-
If you use **TadGAN** for your research, please consider citing the following paper:
Alexander Geiger, Dongyu Liu, Sarah Alnegheimish, Alfredo Cuesta-Infante, Kalyan Veeramachaneni. [TadGAN - Time Series Anomaly Detection Using Generative Adversarial Networks](https://arxiv.org/pdf/2009.07769v3.pdf).
@@ -183,3 +180,20 @@ Alexander Geiger, Dongyu Liu, Sarah Alnegheimish, Alfredo Cuesta-Infante, Kalyan
year={2020}
}
```
+
+If you use **Orion** which is part of the **Sintel** ecosystem for your research, please consider citing the following paper:
+
+Sarah Alnegheimish, Dongyu Liu, Carles Sala, Laure Berti-Equille, Kalyan Veeramachaneni. [Sintel: A Machine Learning Framework to Extract Insights from Signals](https://dl.acm.org/doi/pdf/10.1145/3514221.3517910).
+```
+@inproceedings{alnegheimish2022sintel,
+ title={Sintel: A Machine Learning Framework to Extract Insights from Signals},
+ author={Alnegheimish, Sarah and Liu, Dongyu and Sala, Carles and Berti-Equille, Laure and Veeramachaneni, Kalyan},
+ booktitle={Proceedings of the 2022 International Conference on Management of Data},
+ pages={1855–1865},
+ numpages={11},
+ publisher={Association for Computing Machinery},
+ doi={10.1145/3514221.3517910},
+ series={SIGMOD '22},
+ year={2022}
+}
+```
diff --git a/benchmark/leaderboard.md b/benchmark/leaderboard.md
index 00921ec9..ab9f2b94 100644
--- a/benchmark/leaderboard.md
+++ b/benchmark/leaderboard.md
@@ -2,8 +2,9 @@
|---------------------------|--------------------|
| AER | 10 |
| TadGAN | 7 |
-| LSTM Dynamic Thresholding | 8 |
+| LSTM Dynamic Thresholding | 7 |
| LSTM Autoencoder | 6 |
| Dense Autoencoder | 6 |
| VAE | 6 |
+| GANF | 6 |
| Azure | 0 |
diff --git a/benchmark/leaderboard.xlsx b/benchmark/leaderboard.xlsx
index 370f5c8c..b3eda4bc 100644
Binary files a/benchmark/leaderboard.xlsx and b/benchmark/leaderboard.xlsx differ
diff --git a/benchmark/results/0.4.1.csv b/benchmark/results/0.4.1.csv
new file mode 100644
index 00000000..97ce8fcc
--- /dev/null
+++ b/benchmark/results/0.4.1.csv
@@ -0,0 +1,4429 @@
+dataset,pipeline,signal,iteration,f1,recall,precision,tn,fp,fn,tp,status,elapsed,split,run_id
+MSL,aer,C-1,0,0.3333333333333333,0.5,0.25,,3,1,1,OK,102.017227,True,316e0a96-f
+MSL,aer,C-2,0,,0.0,,,0,2,0,OK,38.773592,True,316e0a96-f
+MSL,aer,D-14,0,1.0,1.0,1.0,,0,0,2,OK,84.672574,True,316e0a96-f
+MSL,aer,D-15,0,,0.0,,,0,1,0,OK,98.49705300000001,True,316e0a96-f
+MSL,aer,D-16,0,1.0,1.0,1.0,,0,0,1,OK,60.252935,True,316e0a96-f
+MSL,aer,F-4,0,,0.0,0.0,,3,1,0,OK,108.02936100000001,True,316e0a96-f
+MSL,aer,F-5,0,0.6666666666666666,1.0,0.5,,1,0,1,OK,91.806166,True,316e0a96-f
+MSL,aer,F-7,0,,0.0,,,0,3,0,OK,117.534123,True,316e0a96-f
+MSL,aer,F-8,0,0.5,1.0,0.3333333333333333,,2,0,1,OK,155.280529,True,316e0a96-f
+MSL,aer,M-1,0,1.0,1.0,1.0,,0,0,1,OK,102.76584799999999,True,316e0a96-f
+MSL,aer,M-2,0,,0.0,,,0,1,0,OK,101.08694100000001,True,316e0a96-f
+MSL,aer,M-3,0,,0.0,,,0,1,0,OK,97.182512,True,316e0a96-f
+MSL,aer,M-4,0,,0.0,,,0,1,0,OK,98.20293000000001,True,316e0a96-f
+MSL,aer,M-5,0,,0.0,,,0,1,0,OK,92.22419599999999,True,316e0a96-f
+MSL,aer,M-6,0,1.0,1.0,1.0,,0,0,1,OK,61.76221700000001,True,316e0a96-f
+MSL,aer,M-7,0,0.6666666666666666,1.0,0.5,,1,0,1,OK,50.60904,True,316e0a96-f
+MSL,aer,P-10,0,1.0,1.0,1.0,,0,0,1,OK,119.08871299999998,True,316e0a96-f
+MSL,aer,P-11,0,0.8,1.0,0.6666666666666666,,1,0,2,OK,183.803924,True,316e0a96-f
+MSL,aer,P-14,0,1.0,1.0,1.0,,0,0,1,OK,88.935022,True,316e0a96-f
+MSL,aer,P-15,0,1.0,1.0,1.0,,0,0,1,OK,166.268223,True,316e0a96-f
+MSL,aer,S-2,0,1.0,1.0,1.0,,0,0,1,OK,40.564146,True,316e0a96-f
+MSL,aer,T-12,0,,0.0,0.0,,2,1,0,OK,32.851786,True,316e0a96-f
+MSL,aer,T-13,0,0.6666666666666666,0.5,1.0,,0,1,1,OK,56.373842,True,316e0a96-f
+MSL,aer,T-4,0,1.0,1.0,1.0,,0,0,1,OK,104.608731,True,316e0a96-f
+MSL,aer,T-5,0,1.0,1.0,1.0,,0,0,1,OK,62.66025500000001,True,316e0a96-f
+MSL,aer,T-8,0,0.6666666666666666,1.0,0.5,,2,0,2,OK,38.580114,True,316e0a96-f
+MSL,aer,T-9,0,0.6666666666666666,0.5,1.0,,0,1,1,OK,25.073489000000002,True,316e0a96-f
+SMAP,aer,A-1,0,1.0,1.0,1.0,,0,0,1,OK,74.686615,True,316e0a96-f
+SMAP,aer,A-2,0,,0.0,,,0,1,0,OK,134.727169,True,316e0a96-f
+SMAP,aer,A-3,0,0.6666666666666666,1.0,0.5,,1,0,1,OK,137.905928,True,316e0a96-f
+SMAP,aer,A-4,0,1.0,1.0,1.0,,0,0,1,OK,108.81877,True,316e0a96-f
+SMAP,aer,A-5,0,1.0,1.0,1.0,,0,0,1,OK,33.840332000000004,True,316e0a96-f
+SMAP,aer,A-6,0,1.0,1.0,1.0,,0,0,1,OK,33.859617,True,316e0a96-f
+SMAP,aer,A-7,0,1.0,1.0,1.0,,0,0,1,OK,141.239304,True,316e0a96-f
+SMAP,aer,A-8,0,1.0,1.0,1.0,,0,0,1,OK,51.285274,True,316e0a96-f
+SMAP,aer,A-9,0,1.0,1.0,1.0,,0,0,1,OK,51.251837,True,316e0a96-f
+SMAP,aer,B-1,0,0.6666666666666666,1.0,0.5,,1,0,1,OK,88.77266999999999,True,316e0a96-f
+SMAP,aer,D-1,0,1.0,1.0,1.0,,0,0,1,OK,140.078624,True,316e0a96-f
+SMAP,aer,D-11,0,1.0,1.0,1.0,,0,0,1,OK,126.416839,True,316e0a96-f
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+SMAP,aer,D-13,0,0.6666666666666666,1.0,0.5,,1,0,1,OK,61.513895,True,316e0a96-f
+SMAP,aer,D-2,0,1.0,1.0,1.0,,0,0,1,OK,76.93292199999999,True,316e0a96-f
+SMAP,aer,D-3,0,1.0,1.0,1.0,,0,0,1,OK,135.331046,True,316e0a96-f
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+SMAP,aer,D-8,0,1.0,1.0,1.0,,0,0,1,OK,72.016047,True,316e0a96-f
+SMAP,aer,D-9,0,1.0,1.0,1.0,,0,0,1,OK,65.829514,True,316e0a96-f
+SMAP,aer,E-1,0,1.0,1.0,1.0,,0,0,2,OK,146.96119099999999,True,316e0a96-f
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+SMAP,aer,E-11,0,1.0,1.0,1.0,,0,0,2,OK,148.12748100000002,True,316e0a96-f
+SMAP,aer,E-12,0,0.5,0.5,0.5,,1,1,1,OK,146.144687,True,316e0a96-f
+SMAP,aer,E-13,0,0.5,0.3333333333333333,1.0,,0,2,1,OK,146.233919,True,316e0a96-f
+SMAP,aer,E-2,0,1.0,1.0,1.0,,0,0,1,OK,146.788419,True,316e0a96-f
+SMAP,aer,E-3,0,1.0,1.0,1.0,,0,0,1,OK,140.85241499999998,True,316e0a96-f
+SMAP,aer,E-4,0,,0.0,0.0,,2,1,0,OK,143.390595,True,316e0a96-f
+SMAP,aer,E-5,0,,0.0,,,0,1,0,OK,147.11121,True,316e0a96-f
+SMAP,aer,E-6,0,1.0,1.0,1.0,,0,0,1,OK,146.89346,True,316e0a96-f
+SMAP,aer,E-7,0,1.0,1.0,1.0,,0,0,1,OK,141.731663,True,316e0a96-f
+SMAP,aer,E-8,0,1.0,1.0,1.0,,0,0,1,OK,144.147031,True,316e0a96-f
+SMAP,aer,E-9,0,1.0,1.0,1.0,,0,0,1,OK,144.893797,True,316e0a96-f
+SMAP,aer,F-1,0,,0.0,0.0,,1,1,0,OK,142.995395,True,316e0a96-f
+SMAP,aer,F-2,0,1.0,1.0,1.0,,0,0,1,OK,80.00886,True,316e0a96-f
+SMAP,aer,F-3,0,,0.0,,,0,1,0,OK,102.730746,True,316e0a96-f
+SMAP,aer,G-1,0,,0.0,0.0,,1,1,0,OK,111.41546699999999,True,316e0a96-f
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+SMAP,aer,P-4,0,1.0,1.0,1.0,,0,0,3,OK,92.704574,True,316e0a96-f
+SMAP,aer,P-7,0,1.0,1.0,1.0,,0,0,1,OK,105.774934,True,316e0a96-f
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+SMAP,aer,T-3,0,1.0,1.0,1.0,,0,0,2,OK,139.647231,True,316e0a96-f
+YAHOOA1,aer,real_1,0,1.0,1.0,1.0,,0,0,2,OK,45.305004,False,316e0a96-f
+YAHOOA1,aer,real_10,0,1.0,1.0,1.0,,0,0,1,OK,68.397841,False,316e0a96-f
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+YAHOOA1,aer,real_13,0,1.0,1.0,1.0,,0,0,3,OK,70.039798,False,316e0a96-f
+YAHOOA1,aer,real_14,0,0.5,1.0,0.3333333333333333,,2,0,1,OK,61.336732999999995,False,316e0a96-f
+YAHOOA1,aer,real_15,0,0.8,0.6666666666666666,1.0,,0,1,2,OK,68.419726,False,316e0a96-f
+YAHOOA1,aer,real_16,0,1.0,1.0,1.0,,0,0,1,OK,43.112678,False,316e0a96-f
+YAHOOA1,aer,real_17,0,0.8,0.6666666666666666,1.0,,0,1,2,OK,67.905458,False,316e0a96-f
+YAHOOA1,aer,real_18,0,0.5,1.0,0.3333333333333333,,2,0,1,OK,61.355414,False,316e0a96-f
+YAHOOA1,aer,real_19,0,0.8,0.6666666666666666,1.0,,0,1,2,OK,68.471336,False,316e0a96-f
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+YAHOOA1,aer,real_20,0,0.6666666666666666,0.6666666666666666,0.6666666666666666,,1,1,2,OK,69.036564,False,316e0a96-f
+YAHOOA1,aer,real_21,0,1.0,1.0,1.0,,0,0,2,OK,47.864937,False,316e0a96-f
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+YAHOOA1,aer,real_24,0,1.0,1.0,1.0,,0,0,3,OK,54.917260999999996,False,316e0a96-f
+YAHOOA1,aer,real_25,0,0.6666666666666666,1.0,0.5,,1,0,1,OK,50.731808,False,316e0a96-f
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+realTweets,vae,Twitter_volume_KO,0,0.8,0.6666666666666666,1.0,,0,1,2,OK,447.11818099999994,False,aec26afb-0
+realTweets,vae,Twitter_volume_PFE,0,0.4,0.25,1.0,,0,3,1,OK,487.331628,False,aec26afb-0
+realTweets,vae,Twitter_volume_UPS,0,,0.0,0.0,,1,5,0,OK,393.924981,False,aec26afb-0
diff --git a/docs/user_guides/primitives_pipelines/pipelines.rst b/docs/user_guides/primitives_pipelines/pipelines.rst
index e537533d..3a768077 100644
--- a/docs/user_guides/primitives_pipelines/pipelines.rst
+++ b/docs/user_guides/primitives_pipelines/pipelines.rst
@@ -8,7 +8,7 @@ The main component in the Orion project are the **Orion Pipelines**, which consi
As ``MLPipeline`` instances, **Orion Pipelines**:
-* consist of a list of one or more `MLPrimitives `__
+* consist of a list of one or more `mlstars `__
* can be *fitted* on some data and later on used to *predict* anomalies on more data
* can be *scored* by comparing their predictions with some known anomalies
* have *hyperparameters* that can be *tuned* to improve their anomaly detection performance
@@ -153,7 +153,7 @@ Since pipelines are composed of :ref:`primitives`, you can discover the interpre
"value": np.random.randint(0, 10, 500)})
hyperparameters = {
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"interval": 300
},
'keras.Sequential.LSTMTimeSeriesRegressor#1': {
diff --git a/docs/user_guides/primitives_pipelines/primitives.rst b/docs/user_guides/primitives_pipelines/primitives.rst
index e83f57a7..027cff7e 100644
--- a/docs/user_guides/primitives_pipelines/primitives.rst
+++ b/docs/user_guides/primitives_pipelines/primitives.rst
@@ -4,7 +4,7 @@
Primitives
==========
-Primitives are data processing units. They are defined by the code that performs the actual processing and an annotated ``json`` file. To read more about primitives and their composition, visit `MLPrimitives `__.
+Primitives are data processing units. They are defined by the code that performs the actual processing and an annotated ``json`` file. To read more about primitives and their composition, visit `mlstars `__.
Preprocessing
-------------
diff --git a/docs/user_guides/primitives_pipelines/primitives/AER.rst b/docs/user_guides/primitives_pipelines/primitives/AER.rst
index fc92b66a..3f0e6d19 100644
--- a/docs/user_guides/primitives_pipelines/primitives/AER.rst
+++ b/docs/user_guides/primitives_pipelines/primitives/AER.rst
@@ -40,7 +40,7 @@ argument type description
:okwarning:
import numpy as np
- from mlprimitives import load_primitive
+ from mlstars import load_primitive
X = np.ones((64, 100, 1))
y = X[:,:, [0]] # signal to reconstruct from X (channel 0)
diff --git a/docs/user_guides/primitives_pipelines/primitives/DenseSeq2Seq.rst b/docs/user_guides/primitives_pipelines/primitives/DenseSeq2Seq.rst
index 93f6c433..ee7be16d 100644
--- a/docs/user_guides/primitives_pipelines/primitives/DenseSeq2Seq.rst
+++ b/docs/user_guides/primitives_pipelines/primitives/DenseSeq2Seq.rst
@@ -47,7 +47,7 @@ argument type description
:okwarning:
import numpy as np
- from mlprimitives import load_primitive
+ from mlstars import load_primitive
X = np.array([1] * 100).reshape(1, -1, 1)
diff --git a/docs/user_guides/primitives_pipelines/primitives/LSTMSeq2Seq.rst b/docs/user_guides/primitives_pipelines/primitives/LSTMSeq2Seq.rst
index 00c71578..dd3c1516 100644
--- a/docs/user_guides/primitives_pipelines/primitives/LSTMSeq2Seq.rst
+++ b/docs/user_guides/primitives_pipelines/primitives/LSTMSeq2Seq.rst
@@ -49,7 +49,7 @@ argument type description
:okwarning:
import numpy as np
- from mlprimitives import load_primitive
+ from mlstars import load_primitive
X = np.array([1] * 100).reshape(1, -1, 1)
diff --git a/docs/user_guides/primitives_pipelines/primitives/LSTMTimeSeriesRegressor.rst b/docs/user_guides/primitives_pipelines/primitives/LSTMTimeSeriesRegressor.rst
index 1f16be70..d5ca166f 100644
--- a/docs/user_guides/primitives_pipelines/primitives/LSTMTimeSeriesRegressor.rst
+++ b/docs/user_guides/primitives_pipelines/primitives/LSTMTimeSeriesRegressor.rst
@@ -7,7 +7,7 @@ LSTM
**description**: this is a prediction model with double stacked LSTM layers used as a time series regressor. you can read more about it in the `related paper `__.
-see `json `__.
+see `json `__.
====================== =================== ===========================================================================================================================================
argument type description
@@ -48,7 +48,7 @@ argument type description
:okwarning:
import numpy as np
- from mlprimitives import load_primitive
+ from mlstars import load_primitive
X = np.array([1] * 100).reshape(1, -1, 1)
y = np.array([[1]])
diff --git a/docs/user_guides/primitives_pipelines/primitives/MinMaxScaler.rst b/docs/user_guides/primitives_pipelines/primitives/MinMaxScaler.rst
index 6cb9d1b8..d31e4b74 100644
--- a/docs/user_guides/primitives_pipelines/primitives/MinMaxScaler.rst
+++ b/docs/user_guides/primitives_pipelines/primitives/MinMaxScaler.rst
@@ -7,7 +7,7 @@ MinMaxScaler
**description**: this primitive transforms features by scaling each feature to a given range.
-see `json `__.
+see `json `__.
==================== =================== =============================================================================================================
argument type description
@@ -33,7 +33,7 @@ argument type description
:okwarning:
import numpy as np
- from mlprimitives import load_primitive
+ from mlstars import load_primitive
X = np.array(range(5)).reshape(-1, 1)
primitive = load_primitive('sklearn.preprocessing.MinMaxScaler',
diff --git a/docs/user_guides/primitives_pipelines/primitives/SimpleImputer.rst b/docs/user_guides/primitives_pipelines/primitives/SimpleImputer.rst
index c59f4f78..000992e0 100644
--- a/docs/user_guides/primitives_pipelines/primitives/SimpleImputer.rst
+++ b/docs/user_guides/primitives_pipelines/primitives/SimpleImputer.rst
@@ -7,7 +7,7 @@ SimpleImputer
**description**: this primitive is an imputation transformer for filling missing values.
-see `json `__.
+see `json `__.
==================== ========================================================= ==========================================
argument type description
@@ -35,7 +35,7 @@ argument type
:okwarning:
import numpy as np
- from mlprimitives import load_primitive
+ from mlstars import load_primitive
X = np.array([1] * 4 + [np.nan]).reshape(-1, 1)
primitive = load_primitive('sklearn.impute.SimpleImputer',
diff --git a/docs/user_guides/primitives_pipelines/primitives/TadGAN.rst b/docs/user_guides/primitives_pipelines/primitives/TadGAN.rst
index 7d418023..baf4a7f0 100644
--- a/docs/user_guides/primitives_pipelines/primitives/TadGAN.rst
+++ b/docs/user_guides/primitives_pipelines/primitives/TadGAN.rst
@@ -44,7 +44,7 @@ argument type description
:okwarning:
import numpy as np
- from mlprimitives import load_primitive
+ from mlstars import load_primitive
X = np.array([1] * 100).reshape(1, -1, 1)
y = X[:,:, [0]] # signal to reconstruct from X (channel 0)
diff --git a/docs/user_guides/primitives_pipelines/primitives/VAE.rst b/docs/user_guides/primitives_pipelines/primitives/VAE.rst
index c9cbdcfd..590d2f5e 100644
--- a/docs/user_guides/primitives_pipelines/primitives/VAE.rst
+++ b/docs/user_guides/primitives_pipelines/primitives/VAE.rst
@@ -46,7 +46,7 @@ argument type description
:okwarning:
import numpy as np
- from mlprimitives import load_primitive
+ from mlstars import load_primitive
X = np.array([1] * 100).reshape(1, -1, 1)
diff --git a/docs/user_guides/primitives_pipelines/primitives/arima.rst b/docs/user_guides/primitives_pipelines/primitives/arima.rst
index 8ed8c927..0c95e9c1 100644
--- a/docs/user_guides/primitives_pipelines/primitives/arima.rst
+++ b/docs/user_guides/primitives_pipelines/primitives/arima.rst
@@ -7,7 +7,7 @@ ARIMA
**description**: this is an Autoregressive Integrated Moving Average (ARIMA) prediction model.
-see `json `__.
+see `json `__.
==================== =================== ==================================================================
argument type description
@@ -35,7 +35,7 @@ argument type description
:okwarning:
import numpy as np
- from mlprimitives import load_primitive
+ from mlstars import load_primitive
X = np.array(range(100)).reshape(-1, 1)
primitive = load_primitive('statsmodels.tsa.arima_model.Arima',
diff --git a/docs/user_guides/primitives_pipelines/primitives/fillna.rst b/docs/user_guides/primitives_pipelines/primitives/fillna.rst
index 03b7cdd7..df818375 100644
--- a/docs/user_guides/primitives_pipelines/primitives/fillna.rst
+++ b/docs/user_guides/primitives_pipelines/primitives/fillna.rst
@@ -35,7 +35,7 @@ argument type
:okwarning:
import numpy as np
- from mlprimitives import load_primitive
+ from mlstars import load_primitive
X = np.array([1] * 4 + [np.nan]).reshape(-1, 1)
primitive = load_primitive('orion.primitives.timeseries_preprocessing.fillna',
diff --git a/docs/user_guides/primitives_pipelines/primitives/find_anomalies.rst b/docs/user_guides/primitives_pipelines/primitives/find_anomalies.rst
index 4783dd73..6ac0b5ef 100644
--- a/docs/user_guides/primitives_pipelines/primitives/find_anomalies.rst
+++ b/docs/user_guides/primitives_pipelines/primitives/find_anomalies.rst
@@ -39,7 +39,7 @@ argument type description
:okwarning:
import numpy as np
- from mlprimitives import load_primitive
+ from mlstars import load_primitive
primitive = load_primitive('orion.primitives.timeseries_anomalies.find_anomalies',
arguments={"anomaly_padding": 1})
diff --git a/docs/user_guides/primitives_pipelines/primitives/intervals_to_mask.rst b/docs/user_guides/primitives_pipelines/primitives/intervals_to_mask.rst
index ded94c65..6e1c4431 100644
--- a/docs/user_guides/primitives_pipelines/primitives/intervals_to_mask.rst
+++ b/docs/user_guides/primitives_pipelines/primitives/intervals_to_mask.rst
@@ -3,11 +3,11 @@
intervals to mask
~~~~~~~~~~~~~~~~~
-**path**: ``mlprimitives.custom.timeseries_preprocessing.intervals_to_mask``
+**path**: ``mlstars.custom.timeseries_preprocessing.intervals_to_mask``
**description**: this primitive creates boolean mask from given intervals.
-see `json `__.
+see `json `__.
==================== =============================== =================================================================================================================================
argument type description
@@ -28,9 +28,9 @@ argument type description
:okwarning:
import numpy as np
- from mlprimitives import load_primitive
+ from mlstars import load_primitive
- primitive = load_primitive('mlprimitives.custom.timeseries_preprocessing.intervals_to_mask')
+ primitive = load_primitive('mlstars.custom.timeseries_preprocessing.intervals_to_mask')
index = np.array(range(10))
intervals = [(1, 3), (7, 7)]
diff --git a/docs/user_guides/primitives_pipelines/primitives/reconstruction_errors.rst b/docs/user_guides/primitives_pipelines/primitives/reconstruction_errors.rst
index b6df2ad5..2ae7a8fd 100644
--- a/docs/user_guides/primitives_pipelines/primitives/reconstruction_errors.rst
+++ b/docs/user_guides/primitives_pipelines/primitives/reconstruction_errors.rst
@@ -38,7 +38,7 @@ argument type description
:okwarning:
import numpy as np
- from mlprimitives import load_primitive
+ from mlstars import load_primitive
primitive = load_primitive('orion.primitives.timeseries_errors.reconstruction_errors')
y = np.array([[1]] * 100)
diff --git a/docs/user_guides/primitives_pipelines/primitives/regression_errors.rst b/docs/user_guides/primitives_pipelines/primitives/regression_errors.rst
index 00599cf6..1fc751b8 100644
--- a/docs/user_guides/primitives_pipelines/primitives/regression_errors.rst
+++ b/docs/user_guides/primitives_pipelines/primitives/regression_errors.rst
@@ -37,7 +37,7 @@ argument type description
:okwarning:
import numpy as np
- from mlprimitives import load_primitive
+ from mlstars import load_primitive
primitive = load_primitive('orion.primitives.timeseries_errors.regression_errors')
y = np.array([[1]] * 100)
diff --git a/docs/user_guides/primitives_pipelines/primitives/rolling_window_sequences.rst b/docs/user_guides/primitives_pipelines/primitives/rolling_window_sequences.rst
index b65e61bd..14656f43 100644
--- a/docs/user_guides/primitives_pipelines/primitives/rolling_window_sequences.rst
+++ b/docs/user_guides/primitives_pipelines/primitives/rolling_window_sequences.rst
@@ -3,11 +3,11 @@
rolling window sequence
~~~~~~~~~~~~~~~~~~~~~~~
-**path**: ``mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences``
+**path**: ``mlstars.custom.timeseries_preprocessing.rolling_window_sequences``
**description**: this primitive generates many sub-sequences of the original sequence. it uses a rolling window approach to create the sub-sequences out of time series data.
-see `json `__.
+see `json `__.
==================== ============================================================== ==================================================================
argument type description
@@ -41,9 +41,9 @@ see `json `__.
+see `json `__.
==================== =========================================== =============================================================================================================================
argument type description
@@ -28,9 +28,9 @@ argument type description
.. ipython:: python
:okwarning:
- from mlprimitives import load_primitive
+ from mlstars import load_primitive
- primitive = load_primitive('mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate',
+ primitive = load_primitive('mlstars.custom.timeseries_preprocessing.time_segments_aggregate',
arguments={"time_column": "timestamp", "interval":10, "method":'mean'})
df = pd.DataFrame({
diff --git a/orion/__init__.py b/orion/__init__.py
index 16534340..5ac5a29e 100644
--- a/orion/__init__.py
+++ b/orion/__init__.py
@@ -2,7 +2,7 @@
__author__ = """MIT Data To AI Lab"""
__email__ = 'dailabmit@gmail.com'
-__version__ = '0.4.1'
+__version__ = '0.5.0.dev0'
import os
diff --git a/orion/benchmark.py b/orion/benchmark.py
index c0d56ff6..99b733c9 100644
--- a/orion/benchmark.py
+++ b/orion/benchmark.py
@@ -28,7 +28,7 @@
LOGGER = logging.getLogger(__name__)
-BUCKET = 'd3-ai-orion'
+BUCKET = 'sintel-orion'
S3_URL = 'https://{}.s3.amazonaws.com/{}'
BENCHMARK_PATH = os.path.join(os.path.join(
@@ -50,11 +50,11 @@
VERIFIED_PIPELINES_GPU = {
'arima': 'arima',
- 'lstm_dynamic_threshold': 'lstm_dynamic_threshold_gpu',
+ 'lstm_dynamic_threshold': 'lstm_dynamic_threshold',
'azure': 'azure',
'tadgan': 'tadgan_without_dropout_gpu',
'aer': 'aer',
- 'lstm_autoencoder': 'lstm_autoencoder_gpu',
+ 'lstm_autoencoder': 'lstm_autoencoder',
'dense_autoencoder': 'dense_autoencoder',
'vae': 'vae'
}
diff --git a/orion/core.py b/orion/core.py
index 792c1809..f9e6a332 100644
--- a/orion/core.py
+++ b/orion/core.py
@@ -278,6 +278,8 @@ def evaluate(self, data: pd.DataFrame, ground_truth: pd.DataFrame, fit: bool = F
else:
if not self._fitted:
mlpipeline = self._get_mlpipeline()
+ else:
+ mlpipeline = self._mlpipeline
if train_data is not None:
# Fit first and then predict
diff --git a/orion/data.py b/orion/data.py
index 1be8bc35..4afdedc6 100644
--- a/orion/data.py
+++ b/orion/data.py
@@ -24,7 +24,7 @@
os.path.dirname(os.path.abspath(__file__)),
'data'
)
-BUCKET = 'd3-ai-orion'
+BUCKET = 'sintel-orion'
S3_URL = 'https://{}.s3.amazonaws.com/{}'
NASA_SIGNALS = (
diff --git a/orion/pipelines/sandbox/vae/vae_artificialwithanomaly.json b/orion/pipelines/sandbox/vae/vae_artificialwithanomaly.json
deleted file mode 100644
index 95c8759e..00000000
--- a/orion/pipelines/sandbox/vae/vae_artificialwithanomaly.json
+++ /dev/null
@@ -1,6 +0,0 @@
-{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
- "time_column": "timestamp",
- "interval": 600
- }
-}
diff --git a/orion/pipelines/sandbox/vae/vae_msl.json b/orion/pipelines/sandbox/vae/vae_msl.json
deleted file mode 100644
index d710250c..00000000
--- a/orion/pipelines/sandbox/vae/vae_msl.json
+++ /dev/null
@@ -1,6 +0,0 @@
-{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
- "time_column": "timestamp",
- "interval": 21600
- }
-}
diff --git a/orion/pipelines/sandbox/vae/vae_realadexchange.json b/orion/pipelines/sandbox/vae/vae_realadexchange.json
deleted file mode 100644
index 0cdc3856..00000000
--- a/orion/pipelines/sandbox/vae/vae_realadexchange.json
+++ /dev/null
@@ -1,6 +0,0 @@
-{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
- "time_column": "timestamp",
- "interval": 3600
- }
-}
diff --git a/orion/pipelines/sandbox/vae/vae_realawscloudwatch.json b/orion/pipelines/sandbox/vae/vae_realawscloudwatch.json
deleted file mode 100644
index 95c8759e..00000000
--- a/orion/pipelines/sandbox/vae/vae_realawscloudwatch.json
+++ /dev/null
@@ -1,6 +0,0 @@
-{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
- "time_column": "timestamp",
- "interval": 600
- }
-}
diff --git a/orion/pipelines/sandbox/vae/vae_realtraffic.json b/orion/pipelines/sandbox/vae/vae_realtraffic.json
deleted file mode 100644
index 95c8759e..00000000
--- a/orion/pipelines/sandbox/vae/vae_realtraffic.json
+++ /dev/null
@@ -1,6 +0,0 @@
-{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
- "time_column": "timestamp",
- "interval": 600
- }
-}
diff --git a/orion/pipelines/sandbox/vae/vae_realtweets.json b/orion/pipelines/sandbox/vae/vae_realtweets.json
deleted file mode 100644
index 95c8759e..00000000
--- a/orion/pipelines/sandbox/vae/vae_realtweets.json
+++ /dev/null
@@ -1,6 +0,0 @@
-{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
- "time_column": "timestamp",
- "interval": 600
- }
-}
diff --git a/orion/pipelines/sandbox/vae/vae_smap.json b/orion/pipelines/sandbox/vae/vae_smap.json
deleted file mode 100644
index d710250c..00000000
--- a/orion/pipelines/sandbox/vae/vae_smap.json
+++ /dev/null
@@ -1,6 +0,0 @@
-{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
- "time_column": "timestamp",
- "interval": 21600
- }
-}
diff --git a/orion/pipelines/sandbox/vae/vae_yahooa1.json b/orion/pipelines/sandbox/vae/vae_yahooa1.json
deleted file mode 100644
index 6d2255f1..00000000
--- a/orion/pipelines/sandbox/vae/vae_yahooa1.json
+++ /dev/null
@@ -1,6 +0,0 @@
-{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
- "time_column": "timestamp",
- "interval": 1
- }
-}
diff --git a/orion/pipelines/sandbox/vae/vae_yahooa2.json b/orion/pipelines/sandbox/vae/vae_yahooa2.json
deleted file mode 100644
index 6d2255f1..00000000
--- a/orion/pipelines/sandbox/vae/vae_yahooa2.json
+++ /dev/null
@@ -1,6 +0,0 @@
-{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
- "time_column": "timestamp",
- "interval": 1
- }
-}
diff --git a/orion/pipelines/sandbox/vae/vae_yahooa3.json b/orion/pipelines/sandbox/vae/vae_yahooa3.json
deleted file mode 100644
index 6d2255f1..00000000
--- a/orion/pipelines/sandbox/vae/vae_yahooa3.json
+++ /dev/null
@@ -1,6 +0,0 @@
-{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
- "time_column": "timestamp",
- "interval": 1
- }
-}
diff --git a/orion/pipelines/sandbox/vae/vae_yahooa4.json b/orion/pipelines/sandbox/vae/vae_yahooa4.json
deleted file mode 100644
index 6d2255f1..00000000
--- a/orion/pipelines/sandbox/vae/vae_yahooa4.json
+++ /dev/null
@@ -1,6 +0,0 @@
-{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
- "time_column": "timestamp",
- "interval": 1
- }
-}
diff --git a/orion/pipelines/verified/aer/aer.json b/orion/pipelines/verified/aer/aer.json
index 2c3479a1..e0c8b918 100644
--- a/orion/pipelines/verified/aer/aer.json
+++ b/orion/pipelines/verified/aer/aer.json
@@ -1,16 +1,16 @@
{
"primitives": [
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate",
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate",
"sklearn.impute.SimpleImputer",
"sklearn.preprocessing.MinMaxScaler",
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences",
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences",
"orion.primitives.timeseries_preprocessing.slice_array_by_dims",
"orion.primitives.aer.AER",
"orion.primitives.aer.score_anomalies",
"orion.primitives.timeseries_anomalies.find_anomalies"
],
"init_params": {
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 21600,
"method": "mean"
@@ -21,7 +21,7 @@
1
]
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 100,
"target_size": 1
@@ -51,7 +51,7 @@
}
},
"output_names": {
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"index": "X_index",
"target_index": "y_index"
}
diff --git a/orion/pipelines/verified/aer/aer_artificialwithanomaly.json b/orion/pipelines/verified/aer/aer_artificialwithanomaly.json
index e30ca453..cd049716 100644
--- a/orion/pipelines/verified/aer/aer_artificialwithanomaly.json
+++ b/orion/pipelines/verified/aer/aer_artificialwithanomaly.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 600,
"method": "mean"
diff --git a/orion/pipelines/verified/aer/aer_msl.json b/orion/pipelines/verified/aer/aer_msl.json
index 0163c11c..ac14cfec 100644
--- a/orion/pipelines/verified/aer/aer_msl.json
+++ b/orion/pipelines/verified/aer/aer_msl.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 21600,
"method": "mean"
diff --git a/orion/pipelines/verified/aer/aer_realadexchange.json b/orion/pipelines/verified/aer/aer_realadexchange.json
index d56739fc..a41eb356 100644
--- a/orion/pipelines/verified/aer/aer_realadexchange.json
+++ b/orion/pipelines/verified/aer/aer_realadexchange.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 3600,
"method": "mean"
diff --git a/orion/pipelines/verified/aer/aer_realawscloudwatch.json b/orion/pipelines/verified/aer/aer_realawscloudwatch.json
index 21d489a9..7e286ec0 100644
--- a/orion/pipelines/verified/aer/aer_realawscloudwatch.json
+++ b/orion/pipelines/verified/aer/aer_realawscloudwatch.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 600,
"method": "mean"
diff --git a/orion/pipelines/verified/aer/aer_realtraffic.json b/orion/pipelines/verified/aer/aer_realtraffic.json
index e30ca453..cd049716 100644
--- a/orion/pipelines/verified/aer/aer_realtraffic.json
+++ b/orion/pipelines/verified/aer/aer_realtraffic.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 600,
"method": "mean"
diff --git a/orion/pipelines/verified/aer/aer_realtweets.json b/orion/pipelines/verified/aer/aer_realtweets.json
index 7f42b5fd..aaf67f67 100644
--- a/orion/pipelines/verified/aer/aer_realtweets.json
+++ b/orion/pipelines/verified/aer/aer_realtweets.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 600,
"method": "mean"
diff --git a/orion/pipelines/verified/aer/aer_smap.json b/orion/pipelines/verified/aer/aer_smap.json
index 0163c11c..ac14cfec 100644
--- a/orion/pipelines/verified/aer/aer_smap.json
+++ b/orion/pipelines/verified/aer/aer_smap.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 21600,
"method": "mean"
diff --git a/orion/pipelines/verified/aer/aer_viz.json b/orion/pipelines/verified/aer/aer_viz.json
new file mode 100644
index 00000000..ca2e0a53
--- /dev/null
+++ b/orion/pipelines/verified/aer/aer_viz.json
@@ -0,0 +1,73 @@
+{
+ "primitives": [
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate",
+ "sklearn.impute.SimpleImputer",
+ "sklearn.preprocessing.MinMaxScaler",
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences",
+ "orion.primitives.timeseries_preprocessing.slice_array_by_dims",
+ "orion.primitives.aer.AER",
+ "orion.primitives.aer.score_anomalies",
+ "orion.primitives.timeseries_anomalies.find_anomalies"
+ ],
+ "init_params": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "time_column": "timestamp",
+ "interval": 21600,
+ "method": "mean"
+ },
+ "sklearn.preprocessing.MinMaxScaler#1": {
+ "feature_range": [
+ -1,
+ 1
+ ]
+ },
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "target_column": 0,
+ "window_size": 100,
+ "target_size": 1
+ },
+ "orion.primitives.timeseries_preprocessing.slice_array_by_dims": {
+ "target_index": 0,
+ "axis": 2
+ },
+ "orion.primitives.aer.AER#1": {
+ "epochs": 35
+ },
+ "orion.primitives.aer.score_anomalies#1": {
+ "rec_error_type": "dtw",
+ "comb": "mult",
+ "mask": true,
+ "lambda_rec": 0.5
+ },
+ "orion.primitives.timeseries_anomalies.find_anomalies#1": {
+ "window_size_portion": 0.33,
+ "window_step_size_portion": 0.1,
+ "fixed_threshold": true
+ }
+ },
+ "input_names": {
+ "orion.primitives.timeseries_anomalies.find_anomalies#1": {
+ "index": "index"
+ }
+ },
+ "output_names": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "index": "X_index",
+ "target_index": "y_index"
+ }
+ },
+ "outputs": {
+ "default": [
+ {
+ "name": "events",
+ "variable": "orion.primitives.timeseries_anomalies.find_anomalies#1.y"
+ }
+ ],
+ "visualization": [
+ {
+ "name": "generated_timeseries",
+ "variable": "orion.primitives.aer.AER#1.y_hat"
+ }
+ ]
+ }
+}
diff --git a/orion/pipelines/verified/aer/aer_yahooa1.json b/orion/pipelines/verified/aer/aer_yahooa1.json
index 609e98e1..933c5449 100644
--- a/orion/pipelines/verified/aer/aer_yahooa1.json
+++ b/orion/pipelines/verified/aer/aer_yahooa1.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 1,
"method": "mean"
diff --git a/orion/pipelines/verified/aer/aer_yahooa2.json b/orion/pipelines/verified/aer/aer_yahooa2.json
index ed19fc1d..73b0e2bc 100644
--- a/orion/pipelines/verified/aer/aer_yahooa2.json
+++ b/orion/pipelines/verified/aer/aer_yahooa2.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 1,
"method": "mean"
diff --git a/orion/pipelines/verified/aer/aer_yahooa3.json b/orion/pipelines/verified/aer/aer_yahooa3.json
index 51d7cc4d..4a354ca1 100644
--- a/orion/pipelines/verified/aer/aer_yahooa3.json
+++ b/orion/pipelines/verified/aer/aer_yahooa3.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 1,
"method": "mean"
diff --git a/orion/pipelines/verified/aer/aer_yahooa4.json b/orion/pipelines/verified/aer/aer_yahooa4.json
index 51d7cc4d..4a354ca1 100644
--- a/orion/pipelines/verified/aer/aer_yahooa4.json
+++ b/orion/pipelines/verified/aer/aer_yahooa4.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 1,
"method": "mean"
diff --git a/orion/pipelines/verified/arima/arima.json b/orion/pipelines/verified/arima/arima.json
index eb35fba5..e2ce1331 100644
--- a/orion/pipelines/verified/arima/arima.json
+++ b/orion/pipelines/verified/arima/arima.json
@@ -1,16 +1,16 @@
{
"primitives": [
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate",
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate",
"sklearn.impute.SimpleImputer",
"sklearn.preprocessing.MinMaxScaler",
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences",
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences",
"numpy.reshape",
"statsmodels.tsa.arima_model.Arima",
"orion.primitives.timeseries_errors.regression_errors",
"orion.primitives.timeseries_anomalies.find_anomalies"
],
"init_params": {
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 21600,
"method": "mean"
@@ -21,7 +21,7 @@
1
]
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 250
},
diff --git a/orion/pipelines/verified/arima/arima_artificialwithanomaly.json b/orion/pipelines/verified/arima/arima_artificialwithanomaly.json
index 740e510d..a9b59fce 100644
--- a/orion/pipelines/verified/arima/arima_artificialwithanomaly.json
+++ b/orion/pipelines/verified/arima/arima_artificialwithanomaly.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 600,
"method": "mean"
@@ -10,7 +10,7 @@
1
]
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 250
},
diff --git a/orion/pipelines/verified/arima/arima_msl.json b/orion/pipelines/verified/arima/arima_msl.json
index 79e756b3..9287e83d 100644
--- a/orion/pipelines/verified/arima/arima_msl.json
+++ b/orion/pipelines/verified/arima/arima_msl.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 21600,
"method": "mean"
@@ -10,7 +10,7 @@
1
]
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 250
},
diff --git a/orion/pipelines/verified/arima/arima_realadexchange.json b/orion/pipelines/verified/arima/arima_realadexchange.json
index d257d0c8..5a85a79a 100644
--- a/orion/pipelines/verified/arima/arima_realadexchange.json
+++ b/orion/pipelines/verified/arima/arima_realadexchange.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 3600,
"method": "mean"
@@ -10,7 +10,7 @@
1
]
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 250
},
diff --git a/orion/pipelines/verified/arima/arima_realawscloudwatch.json b/orion/pipelines/verified/arima/arima_realawscloudwatch.json
index 740e510d..a9b59fce 100644
--- a/orion/pipelines/verified/arima/arima_realawscloudwatch.json
+++ b/orion/pipelines/verified/arima/arima_realawscloudwatch.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 600,
"method": "mean"
@@ -10,7 +10,7 @@
1
]
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 250
},
diff --git a/orion/pipelines/verified/arima/arima_realtraffic.json b/orion/pipelines/verified/arima/arima_realtraffic.json
index 740e510d..a9b59fce 100644
--- a/orion/pipelines/verified/arima/arima_realtraffic.json
+++ b/orion/pipelines/verified/arima/arima_realtraffic.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 600,
"method": "mean"
@@ -10,7 +10,7 @@
1
]
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 250
},
diff --git a/orion/pipelines/verified/arima/arima_realtweets.json b/orion/pipelines/verified/arima/arima_realtweets.json
index 740e510d..a9b59fce 100644
--- a/orion/pipelines/verified/arima/arima_realtweets.json
+++ b/orion/pipelines/verified/arima/arima_realtweets.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 600,
"method": "mean"
@@ -10,7 +10,7 @@
1
]
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 250
},
diff --git a/orion/pipelines/verified/arima/arima_smap.json b/orion/pipelines/verified/arima/arima_smap.json
index 79e756b3..9287e83d 100644
--- a/orion/pipelines/verified/arima/arima_smap.json
+++ b/orion/pipelines/verified/arima/arima_smap.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 21600,
"method": "mean"
@@ -10,7 +10,7 @@
1
]
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 250
},
diff --git a/orion/pipelines/verified/arima/arima_yahooa1.json b/orion/pipelines/verified/arima/arima_yahooa1.json
index 5775e641..3a5be402 100644
--- a/orion/pipelines/verified/arima/arima_yahooa1.json
+++ b/orion/pipelines/verified/arima/arima_yahooa1.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 1,
"method": "mean"
@@ -10,7 +10,7 @@
1
]
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 250
},
diff --git a/orion/pipelines/verified/arima/arima_yahooa2.json b/orion/pipelines/verified/arima/arima_yahooa2.json
index 5775e641..3a5be402 100644
--- a/orion/pipelines/verified/arima/arima_yahooa2.json
+++ b/orion/pipelines/verified/arima/arima_yahooa2.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 1,
"method": "mean"
@@ -10,7 +10,7 @@
1
]
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 250
},
diff --git a/orion/pipelines/verified/arima/arima_yahooa3.json b/orion/pipelines/verified/arima/arima_yahooa3.json
index 5775e641..3a5be402 100644
--- a/orion/pipelines/verified/arima/arima_yahooa3.json
+++ b/orion/pipelines/verified/arima/arima_yahooa3.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 1,
"method": "mean"
@@ -10,7 +10,7 @@
1
]
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 250
},
diff --git a/orion/pipelines/verified/arima/arima_yahooa4.json b/orion/pipelines/verified/arima/arima_yahooa4.json
index 5775e641..3a5be402 100644
--- a/orion/pipelines/verified/arima/arima_yahooa4.json
+++ b/orion/pipelines/verified/arima/arima_yahooa4.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 1,
"method": "mean"
@@ -10,7 +10,7 @@
1
]
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 250
},
diff --git a/orion/pipelines/verified/azure/azure.json b/orion/pipelines/verified/azure/azure.json
index 84651ed9..75639243 100644
--- a/orion/pipelines/verified/azure/azure.json
+++ b/orion/pipelines/verified/azure/azure.json
@@ -1,13 +1,13 @@
{
"primitives": [
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate",
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate",
"sklearn.impute.SimpleImputer",
"sklearn.preprocessing.MinMaxScaler",
"orion.primitives.azure_anomaly_detector.split_sequence",
"orion.primitives.azure_anomaly_detector.detect_anomalies"
],
"init_params": {
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 21600,
"method": "mean"
diff --git a/orion/pipelines/verified/azure/azure_artificialwithanomaly.json b/orion/pipelines/verified/azure/azure_artificialwithanomaly.json
index 15b4854a..6976478b 100644
--- a/orion/pipelines/verified/azure/azure_artificialwithanomaly.json
+++ b/orion/pipelines/verified/azure/azure_artificialwithanomaly.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 600,
"method": "mean"
diff --git a/orion/pipelines/verified/azure/azure_msl.json b/orion/pipelines/verified/azure/azure_msl.json
index a0559454..16afea09 100644
--- a/orion/pipelines/verified/azure/azure_msl.json
+++ b/orion/pipelines/verified/azure/azure_msl.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 21600,
"method": "mean"
diff --git a/orion/pipelines/verified/azure/azure_realadexchange.json b/orion/pipelines/verified/azure/azure_realadexchange.json
index c7a9ef3f..dbd59e76 100644
--- a/orion/pipelines/verified/azure/azure_realadexchange.json
+++ b/orion/pipelines/verified/azure/azure_realadexchange.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 3600,
"method": "mean"
diff --git a/orion/pipelines/verified/azure/azure_realawscloudwatch.json b/orion/pipelines/verified/azure/azure_realawscloudwatch.json
index 15b4854a..6976478b 100644
--- a/orion/pipelines/verified/azure/azure_realawscloudwatch.json
+++ b/orion/pipelines/verified/azure/azure_realawscloudwatch.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 600,
"method": "mean"
diff --git a/orion/pipelines/verified/azure/azure_realtraffic.json b/orion/pipelines/verified/azure/azure_realtraffic.json
index 15b4854a..6976478b 100644
--- a/orion/pipelines/verified/azure/azure_realtraffic.json
+++ b/orion/pipelines/verified/azure/azure_realtraffic.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 600,
"method": "mean"
diff --git a/orion/pipelines/verified/azure/azure_realtweets.json b/orion/pipelines/verified/azure/azure_realtweets.json
index 15b4854a..6976478b 100644
--- a/orion/pipelines/verified/azure/azure_realtweets.json
+++ b/orion/pipelines/verified/azure/azure_realtweets.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 600,
"method": "mean"
diff --git a/orion/pipelines/verified/azure/azure_smap.json b/orion/pipelines/verified/azure/azure_smap.json
index a0559454..16afea09 100644
--- a/orion/pipelines/verified/azure/azure_smap.json
+++ b/orion/pipelines/verified/azure/azure_smap.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 21600,
"method": "mean"
diff --git a/orion/pipelines/verified/azure/azure_yahooa1.json b/orion/pipelines/verified/azure/azure_yahooa1.json
index 4d35643f..7e166e9d 100644
--- a/orion/pipelines/verified/azure/azure_yahooa1.json
+++ b/orion/pipelines/verified/azure/azure_yahooa1.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 1,
"method": "mean"
diff --git a/orion/pipelines/verified/azure/azure_yahooa2.json b/orion/pipelines/verified/azure/azure_yahooa2.json
index 4d35643f..7e166e9d 100644
--- a/orion/pipelines/verified/azure/azure_yahooa2.json
+++ b/orion/pipelines/verified/azure/azure_yahooa2.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 1,
"method": "mean"
diff --git a/orion/pipelines/verified/azure/azure_yahooa3.json b/orion/pipelines/verified/azure/azure_yahooa3.json
index 4d35643f..7e166e9d 100644
--- a/orion/pipelines/verified/azure/azure_yahooa3.json
+++ b/orion/pipelines/verified/azure/azure_yahooa3.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 1,
"method": "mean"
diff --git a/orion/pipelines/verified/azure/azure_yahooa4.json b/orion/pipelines/verified/azure/azure_yahooa4.json
index 4d35643f..7e166e9d 100644
--- a/orion/pipelines/verified/azure/azure_yahooa4.json
+++ b/orion/pipelines/verified/azure/azure_yahooa4.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 1,
"method": "mean"
diff --git a/orion/pipelines/verified/dense_autoencoder/dense_autoencoder.json b/orion/pipelines/verified/dense_autoencoder/dense_autoencoder.json
index 4e94fba7..2cc25ebf 100644
--- a/orion/pipelines/verified/dense_autoencoder/dense_autoencoder.json
+++ b/orion/pipelines/verified/dense_autoencoder/dense_autoencoder.json
@@ -1,16 +1,16 @@
{
"primitives": [
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate",
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate",
"sklearn.impute.SimpleImputer",
"sklearn.preprocessing.MinMaxScaler",
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences",
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences",
"orion.primitives.timeseries_preprocessing.slice_array_by_dims",
"keras.Sequential.DenseSeq2Seq",
"orion.primitives.timeseries_errors.reconstruction_errors",
"orion.primitives.timeseries_anomalies.find_anomalies"
],
"init_params": {
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 21600,
"method": "mean"
@@ -18,7 +18,7 @@
"sklearn.preprocessing.MinMaxScaler#1": {
"feature_range": [-1, 1]
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 100
},
@@ -43,7 +43,7 @@
"keras.Sequential.DenseSeq2Seq#1": {
"y": "y_hat"
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"index": "X_index",
"target_index": "y_index"
}
diff --git a/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_artificialwithanomaly.json b/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_artificialwithanomaly.json
index 95c8759e..eebcc81d 100644
--- a/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_artificialwithanomaly.json
+++ b/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_artificialwithanomaly.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 600
}
diff --git a/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_msl.json b/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_msl.json
index d710250c..e4fe0c11 100644
--- a/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_msl.json
+++ b/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_msl.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 21600
}
diff --git a/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_realadexchange.json b/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_realadexchange.json
index 0cdc3856..6b8aac0a 100644
--- a/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_realadexchange.json
+++ b/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_realadexchange.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 3600
}
diff --git a/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_realawscloudwatch.json b/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_realawscloudwatch.json
index 95c8759e..eebcc81d 100644
--- a/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_realawscloudwatch.json
+++ b/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_realawscloudwatch.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 600
}
diff --git a/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_realtraffic.json b/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_realtraffic.json
index 95c8759e..eebcc81d 100644
--- a/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_realtraffic.json
+++ b/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_realtraffic.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 600
}
diff --git a/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_realtweets.json b/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_realtweets.json
index 95c8759e..eebcc81d 100644
--- a/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_realtweets.json
+++ b/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_realtweets.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 600
}
diff --git a/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_smap.json b/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_smap.json
index d710250c..e4fe0c11 100644
--- a/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_smap.json
+++ b/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_smap.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 21600
}
diff --git a/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_yahooa1.json b/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_yahooa1.json
index 6d2255f1..0fdb0776 100644
--- a/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_yahooa1.json
+++ b/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_yahooa1.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 1
}
diff --git a/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_yahooa2.json b/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_yahooa2.json
index 6d2255f1..0fdb0776 100644
--- a/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_yahooa2.json
+++ b/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_yahooa2.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 1
}
diff --git a/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_yahooa3.json b/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_yahooa3.json
index 6d2255f1..0fdb0776 100644
--- a/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_yahooa3.json
+++ b/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_yahooa3.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 1
}
diff --git a/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_yahooa4.json b/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_yahooa4.json
index 6d2255f1..0fdb0776 100644
--- a/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_yahooa4.json
+++ b/orion/pipelines/verified/dense_autoencoder/dense_autoencoder_yahooa4.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 1
}
diff --git a/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder.json b/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder.json
index b13bf66a..91c545bd 100644
--- a/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder.json
+++ b/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder.json
@@ -1,16 +1,16 @@
{
"primitives": [
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate",
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate",
"sklearn.impute.SimpleImputer",
"sklearn.preprocessing.MinMaxScaler",
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences",
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences",
"orion.primitives.timeseries_preprocessing.slice_array_by_dims",
"keras.Sequential.LSTMSeq2Seq",
"orion.primitives.timeseries_errors.reconstruction_errors",
"orion.primitives.timeseries_anomalies.find_anomalies"
],
"init_params": {
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 21600,
"method": "mean"
@@ -18,7 +18,7 @@
"sklearn.preprocessing.MinMaxScaler#1": {
"feature_range": [-1, 1]
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 100
},
@@ -43,7 +43,7 @@
"keras.Sequential.LSTMSeq2Seq#1": {
"y": "y_hat"
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"index": "X_index",
"target_index": "y_index"
}
diff --git a/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_artificialwithanomaly.json b/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_artificialwithanomaly.json
index 95c8759e..eebcc81d 100644
--- a/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_artificialwithanomaly.json
+++ b/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_artificialwithanomaly.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 600
}
diff --git a/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_gpu.json b/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_gpu.json
deleted file mode 100644
index 34111ae4..00000000
--- a/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_gpu.json
+++ /dev/null
@@ -1,90 +0,0 @@
-{
- "primitives": [
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate",
- "sklearn.impute.SimpleImputer",
- "sklearn.preprocessing.MinMaxScaler",
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences",
- "orion.primitives.timeseries_preprocessing.slice_array_by_dims",
- "keras.Sequential.LSTMSeq2Seq",
- "orion.primitives.timeseries_errors.reconstruction_errors",
- "orion.primitives.timeseries_anomalies.find_anomalies"
- ],
- "init_params": {
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
- "time_column": "timestamp",
- "interval": 21600,
- "method": "mean"
- },
- "sklearn.preprocessing.MinMaxScaler#1": {
- "feature_range": [-1, 1]
- },
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
- "target_column": 0,
- "window_size": 100
- },
- "orion.primitives.timeseries_preprocessing.slice_array_by_dims": {
- "target_index": 0,
- "axis": 2
- },
- "keras.Sequential.LSTMSeq2Seq#1": {
- "epochs": 35,
- "verbose": false,
- "window_size": 100,
- "input_shape": [100, 1],
- "target_shape": [100, 1],
- "layers": [
- {
- "class": "keras.layers.CuDNNLSTM",
- "parameters": {
- "input_shape": "input_shape",
- "units": 60
- }
- },
- {
- "class": "keras.layers.RepeatVector",
- "parameters": {
- "n": 100
- }
- },
- {
- "class": "keras.layers.CuDNNLSTM",
- "parameters": {
- "units": 60,
- "return_sequences": true
- }
- },
- {
- "class": "keras.layers.TimeDistributed",
- "parameters": {
- "layer": {
- "class": "keras.layers.Dense",
- "parameters": {
- "units": 1
- }
- }
- }
- },
- {
- "class": "keras.layers.Reshape",
- "parameters": {
- "target_shape": "target_shape"
- }
- }
- ]
- },
- "orion.primitives.timeseries_anomalies.find_anomalies#1": {
- "window_size_portion": 0.33,
- "window_step_size_portion": 0.1,
- "fixed_threshold": true
- }
- },
- "output_names": {
- "keras.Sequential.LSTMSeq2Seq#1": {
- "y": "y_hat"
- },
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
- "index": "X_index",
- "target_index": "y_index"
- }
- }
-}
diff --git a/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_msl.json b/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_msl.json
index d710250c..e4fe0c11 100644
--- a/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_msl.json
+++ b/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_msl.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 21600
}
diff --git a/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_realadexchange.json b/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_realadexchange.json
index 0cdc3856..6b8aac0a 100644
--- a/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_realadexchange.json
+++ b/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_realadexchange.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 3600
}
diff --git a/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_realawscloudwatch.json b/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_realawscloudwatch.json
index 95c8759e..eebcc81d 100644
--- a/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_realawscloudwatch.json
+++ b/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_realawscloudwatch.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 600
}
diff --git a/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_realtraffic.json b/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_realtraffic.json
index 95c8759e..eebcc81d 100644
--- a/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_realtraffic.json
+++ b/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_realtraffic.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 600
}
diff --git a/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_realtweets.json b/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_realtweets.json
index 95c8759e..eebcc81d 100644
--- a/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_realtweets.json
+++ b/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_realtweets.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 600
}
diff --git a/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_smap.json b/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_smap.json
index d710250c..e4fe0c11 100644
--- a/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_smap.json
+++ b/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_smap.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 21600
}
diff --git a/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_yahooa1.json b/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_yahooa1.json
index 6d2255f1..0fdb0776 100644
--- a/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_yahooa1.json
+++ b/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_yahooa1.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 1
}
diff --git a/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_yahooa2.json b/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_yahooa2.json
index 6d2255f1..0fdb0776 100644
--- a/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_yahooa2.json
+++ b/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_yahooa2.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 1
}
diff --git a/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_yahooa3.json b/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_yahooa3.json
index 6d2255f1..0fdb0776 100644
--- a/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_yahooa3.json
+++ b/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_yahooa3.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 1
}
diff --git a/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_yahooa4.json b/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_yahooa4.json
index 6d2255f1..0fdb0776 100644
--- a/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_yahooa4.json
+++ b/orion/pipelines/verified/lstm_autoencoder/lstm_autoencoder_yahooa4.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 1
}
diff --git a/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold.json b/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold.json
index 24a9f603..4d87efd6 100644
--- a/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold.json
+++ b/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold.json
@@ -1,15 +1,15 @@
{
"primitives": [
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate",
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate",
"sklearn.impute.SimpleImputer",
"sklearn.preprocessing.MinMaxScaler",
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences",
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences",
"keras.Sequential.LSTMTimeSeriesRegressor",
"orion.primitives.timeseries_errors.regression_errors",
"orion.primitives.timeseries_anomalies.find_anomalies"
],
"init_params": {
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 21600,
"method": "mean"
@@ -20,7 +20,7 @@
1
]
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 250
},
diff --git a/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_artificialwithanomaly.json b/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_artificialwithanomaly.json
index 60a0d19e..e09158f6 100644
--- a/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_artificialwithanomaly.json
+++ b/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_artificialwithanomaly.json
@@ -1,12 +1,12 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 600
},
"sklearn.preprocessing.MinMaxScaler#1": {
"feature_range": [-1, 1]
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 250
},
diff --git a/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_gpu.json b/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_gpu.json
deleted file mode 100644
index 873e2ec4..00000000
--- a/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_gpu.json
+++ /dev/null
@@ -1,83 +0,0 @@
-{
- "primitives": [
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate",
- "sklearn.impute.SimpleImputer",
- "sklearn.preprocessing.MinMaxScaler",
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences",
- "keras.Sequential.LSTMTimeSeriesRegressor",
- "orion.primitives.timeseries_errors.regression_errors",
- "orion.primitives.timeseries_anomalies.find_anomalies"
- ],
- "init_params": {
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
- "time_column": "timestamp",
- "interval": 21600
- },
- "sklearn.preprocessing.MinMaxScaler#1": {
- "feature_range": [
- -1,
- 1
- ]
- },
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
- "target_column": 0,
- "window_size": 250
- },
- "keras.Sequential.LSTMTimeSeriesRegressor": {
- "epochs": 35,
- "verbose": false,
- "layers":
- [
- {
- "class": "keras.layers.CuDNNLSTM",
- "parameters": {
- "input_shape": "input_shape",
- "units": "lstm_1_units",
- "return_sequences": true
- }
- },
- {
- "class": "keras.layers.Dropout",
- "parameters": {
- "rate": "dropout_1_rate"
- }
- },
- {
- "class": "keras.layers.CuDNNLSTM",
- "parameters": {
- "units": "lstm_2_units",
- "return_sequences": false
- }
- },
- {
- "class": "keras.layers.Dropout",
- "parameters": {
- "rate": "dropout_2_rate"
- }
- },
- {
- "class": "keras.layers.Dense",
- "parameters": {
- "units": "dense_units",
- "activation": "linear"
- }
- }
- ]
- },
- "orion.primitives.timeseries_anomalies.find_anomalies#1": {
- "window_size_portion": 0.33,
- "window_step_size_portion": 0.1,
- "fixed_threshold": true
- }
- },
- "input_names": {
- "orion.primitives.timeseries_anomalies.find_anomalies#1": {
- "index": "target_index"
- }
- },
- "output_names": {
- "keras.Sequential.LSTMTimeSeriesRegressor#1": {
- "y": "y_hat"
- }
- }
-}
diff --git a/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_msl.json b/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_msl.json
index 1e503202..e3af2f6c 100644
--- a/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_msl.json
+++ b/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_msl.json
@@ -1,12 +1,12 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 21600
},
"sklearn.preprocessing.MinMaxScaler#1": {
"feature_range": [-1, 1]
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 250
},
diff --git a/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_realadexchange.json b/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_realadexchange.json
index 82a340b2..4e102c19 100644
--- a/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_realadexchange.json
+++ b/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_realadexchange.json
@@ -1,12 +1,12 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 3600
},
"sklearn.preprocessing.MinMaxScaler#1": {
"feature_range": [-1, 1]
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 250
},
diff --git a/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_realawscloudwatch.json b/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_realawscloudwatch.json
index 60a0d19e..e09158f6 100644
--- a/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_realawscloudwatch.json
+++ b/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_realawscloudwatch.json
@@ -1,12 +1,12 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 600
},
"sklearn.preprocessing.MinMaxScaler#1": {
"feature_range": [-1, 1]
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 250
},
diff --git a/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_realtraffic.json b/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_realtraffic.json
index 60a0d19e..e09158f6 100644
--- a/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_realtraffic.json
+++ b/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_realtraffic.json
@@ -1,12 +1,12 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 600
},
"sklearn.preprocessing.MinMaxScaler#1": {
"feature_range": [-1, 1]
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 250
},
diff --git a/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_realtweets.json b/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_realtweets.json
index 60a0d19e..e09158f6 100644
--- a/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_realtweets.json
+++ b/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_realtweets.json
@@ -1,12 +1,12 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 600
},
"sklearn.preprocessing.MinMaxScaler#1": {
"feature_range": [-1, 1]
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 250
},
diff --git a/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_smap.json b/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_smap.json
index 1e503202..e3af2f6c 100644
--- a/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_smap.json
+++ b/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_smap.json
@@ -1,12 +1,12 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 21600
},
"sklearn.preprocessing.MinMaxScaler#1": {
"feature_range": [-1, 1]
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 250
},
diff --git a/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_viz.json b/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_viz.json
index ec69213c..fe755999 100644
--- a/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_viz.json
+++ b/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_viz.json
@@ -1,15 +1,15 @@
{
"primitives": [
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate",
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate",
"sklearn.impute.SimpleImputer",
"sklearn.preprocessing.MinMaxScaler",
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences",
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences",
"keras.Sequential.LSTMTimeSeriesRegressor",
"orion.primitives.timeseries_errors.regression_errors",
"orion.primitives.timeseries_anomalies.find_anomalies"
],
"init_params": {
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 21600,
"method": "mean"
@@ -20,7 +20,7 @@
1
]
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 250
},
diff --git a/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_yahooa1.json b/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_yahooa1.json
index 25a2d283..5be1b006 100644
--- a/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_yahooa1.json
+++ b/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_yahooa1.json
@@ -1,12 +1,12 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 1
},
"sklearn.preprocessing.MinMaxScaler#1": {
"feature_range": [-1, 1]
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 250
},
diff --git a/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_yahooa2.json b/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_yahooa2.json
index 25a2d283..5be1b006 100644
--- a/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_yahooa2.json
+++ b/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_yahooa2.json
@@ -1,12 +1,12 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 1
},
"sklearn.preprocessing.MinMaxScaler#1": {
"feature_range": [-1, 1]
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 250
},
diff --git a/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_yahooa3.json b/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_yahooa3.json
index 25a2d283..5be1b006 100644
--- a/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_yahooa3.json
+++ b/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_yahooa3.json
@@ -1,12 +1,12 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 1
},
"sklearn.preprocessing.MinMaxScaler#1": {
"feature_range": [-1, 1]
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 250
},
diff --git a/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_yahooa4.json b/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_yahooa4.json
index 25a2d283..5be1b006 100644
--- a/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_yahooa4.json
+++ b/orion/pipelines/verified/lstm_dynamic_threshold/lstm_dynamic_threshold_yahooa4.json
@@ -1,12 +1,12 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 1
},
"sklearn.preprocessing.MinMaxScaler#1": {
"feature_range": [-1, 1]
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 250
},
diff --git a/orion/pipelines/verified/lstm_dynamic_threshold/mean_24h_lstm.json b/orion/pipelines/verified/lstm_dynamic_threshold/mean_24h_lstm.json
index 142f0d3b..4d27d7ca 100644
--- a/orion/pipelines/verified/lstm_dynamic_threshold/mean_24h_lstm.json
+++ b/orion/pipelines/verified/lstm_dynamic_threshold/mean_24h_lstm.json
@@ -1,15 +1,15 @@
{
"primitives": [
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate",
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate",
"sklearn.impute.SimpleImputer",
"sklearn.preprocessing.MinMaxScaler",
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences",
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences",
"keras.Sequential.LSTMTimeSeriesRegressor",
"orion.primitives.timeseries_anomalies.regression_errors",
"orion.primitives.timeseries_anomalies.find_anomalies"
],
"init_params": {
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 84600,
"method": "mean"
@@ -20,7 +20,7 @@
1
]
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 250
},
diff --git a/orion/pipelines/verified/lstm_dynamic_threshold/median_24h_lstm.json b/orion/pipelines/verified/lstm_dynamic_threshold/median_24h_lstm.json
index 6fe1d64b..33dfe1e1 100644
--- a/orion/pipelines/verified/lstm_dynamic_threshold/median_24h_lstm.json
+++ b/orion/pipelines/verified/lstm_dynamic_threshold/median_24h_lstm.json
@@ -1,15 +1,15 @@
{
"primitives": [
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate",
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate",
"sklearn.impute.SimpleImputer",
"sklearn.preprocessing.MinMaxScaler",
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences",
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences",
"keras.Sequential.LSTMTimeSeriesRegressor",
"orion.primitives.timeseries_anomalies.regression_errors",
"orion.primitives.timeseries_anomalies.find_anomalies"
],
"init_params": {
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 84600,
"method": "median"
@@ -20,7 +20,7 @@
1
]
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 250
},
diff --git a/orion/pipelines/verified/lstm_dynamic_threshold/skew_24h_lstm.json b/orion/pipelines/verified/lstm_dynamic_threshold/skew_24h_lstm.json
index ef93b99f..9b24ca7b 100644
--- a/orion/pipelines/verified/lstm_dynamic_threshold/skew_24h_lstm.json
+++ b/orion/pipelines/verified/lstm_dynamic_threshold/skew_24h_lstm.json
@@ -1,15 +1,15 @@
{
"primitives": [
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate",
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate",
"sklearn.impute.SimpleImputer",
"sklearn.preprocessing.MinMaxScaler",
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences",
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences",
"keras.Sequential.LSTMTimeSeriesRegressor",
"orion.primitives.timeseries_anomalies.regression_errors",
"orion.primitives.timeseries_anomalies.find_anomalies"
],
"init_params": {
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 84600,
"method": "skew"
@@ -20,7 +20,7 @@
1
]
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 250
},
diff --git a/orion/pipelines/verified/lstm_dynamic_threshold/sum_24h_lstm.json b/orion/pipelines/verified/lstm_dynamic_threshold/sum_24h_lstm.json
index fe5769c9..ad52de45 100644
--- a/orion/pipelines/verified/lstm_dynamic_threshold/sum_24h_lstm.json
+++ b/orion/pipelines/verified/lstm_dynamic_threshold/sum_24h_lstm.json
@@ -1,15 +1,15 @@
{
"primitives": [
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate",
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate",
"sklearn.impute.SimpleImputer",
"sklearn.preprocessing.MinMaxScaler",
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences",
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences",
"keras.Sequential.LSTMTimeSeriesRegressor",
"orion.primitives.timeseries_anomalies.regression_errors",
"orion.primitives.timeseries_anomalies.find_anomalies"
],
"init_params": {
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 84600,
"method": "sum"
@@ -20,7 +20,7 @@
1
]
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 250
},
diff --git a/orion/pipelines/verified/tadgan/tadgan.json b/orion/pipelines/verified/tadgan/tadgan.json
index 797d1bdc..cbda5bd1 100644
--- a/orion/pipelines/verified/tadgan/tadgan.json
+++ b/orion/pipelines/verified/tadgan/tadgan.json
@@ -1,16 +1,16 @@
{
"primitives": [
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate",
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate",
"sklearn.impute.SimpleImputer",
"sklearn.preprocessing.MinMaxScaler",
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences",
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences",
"orion.primitives.timeseries_preprocessing.slice_array_by_dims",
"orion.primitives.tadgan.TadGAN",
"orion.primitives.tadgan.score_anomalies",
"orion.primitives.timeseries_anomalies.find_anomalies"
],
"init_params": {
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 21600,
"method": "mean"
@@ -21,7 +21,7 @@
1
]
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 100,
"target_size": 1
@@ -51,7 +51,7 @@
"orion.primitives.tadgan.TadGAN#1": {
"y": "y_hat"
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"index": "X_index",
"target_index": "y_index"
}
diff --git a/orion/pipelines/verified/tadgan/tadgan_artificialwithanomaly.json b/orion/pipelines/verified/tadgan/tadgan_artificialwithanomaly.json
index 501dc9e4..43fd29e7 100644
--- a/orion/pipelines/verified/tadgan/tadgan_artificialwithanomaly.json
+++ b/orion/pipelines/verified/tadgan/tadgan_artificialwithanomaly.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 600,
"method": "mean"
diff --git a/orion/pipelines/verified/tadgan/tadgan_msl.json b/orion/pipelines/verified/tadgan/tadgan_msl.json
index b5ffac03..9a303c86 100644
--- a/orion/pipelines/verified/tadgan/tadgan_msl.json
+++ b/orion/pipelines/verified/tadgan/tadgan_msl.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 21600,
"method": "mean"
diff --git a/orion/pipelines/verified/tadgan/tadgan_realadexchange.json b/orion/pipelines/verified/tadgan/tadgan_realadexchange.json
index 8cad9f1f..a447aee3 100644
--- a/orion/pipelines/verified/tadgan/tadgan_realadexchange.json
+++ b/orion/pipelines/verified/tadgan/tadgan_realadexchange.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 3600,
"method": "mean"
diff --git a/orion/pipelines/verified/tadgan/tadgan_realawscloudwatch.json b/orion/pipelines/verified/tadgan/tadgan_realawscloudwatch.json
index 077b7b61..d4f238ea 100644
--- a/orion/pipelines/verified/tadgan/tadgan_realawscloudwatch.json
+++ b/orion/pipelines/verified/tadgan/tadgan_realawscloudwatch.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 600,
"method": "mean"
diff --git a/orion/pipelines/verified/tadgan/tadgan_realtraffic.json b/orion/pipelines/verified/tadgan/tadgan_realtraffic.json
index b23563a4..9a17b15e 100644
--- a/orion/pipelines/verified/tadgan/tadgan_realtraffic.json
+++ b/orion/pipelines/verified/tadgan/tadgan_realtraffic.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 600,
"method": "mean"
diff --git a/orion/pipelines/verified/tadgan/tadgan_realtweets.json b/orion/pipelines/verified/tadgan/tadgan_realtweets.json
index b23563a4..9a17b15e 100644
--- a/orion/pipelines/verified/tadgan/tadgan_realtweets.json
+++ b/orion/pipelines/verified/tadgan/tadgan_realtweets.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 600,
"method": "mean"
diff --git a/orion/pipelines/verified/tadgan/tadgan_smap.json b/orion/pipelines/verified/tadgan/tadgan_smap.json
index b5ffac03..9a303c86 100644
--- a/orion/pipelines/verified/tadgan/tadgan_smap.json
+++ b/orion/pipelines/verified/tadgan/tadgan_smap.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 21600,
"method": "mean"
diff --git a/orion/pipelines/verified/tadgan/tadgan_viz.json b/orion/pipelines/verified/tadgan/tadgan_viz.json
index 032266d7..0144dc36 100644
--- a/orion/pipelines/verified/tadgan/tadgan_viz.json
+++ b/orion/pipelines/verified/tadgan/tadgan_viz.json
@@ -1,16 +1,16 @@
{
"primitives": [
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate",
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate",
"sklearn.impute.SimpleImputer",
"sklearn.preprocessing.MinMaxScaler",
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences",
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences",
"orion.primitives.timeseries_preprocessing.slice_array_by_dims",
"orion.primitives.tadgan.TadGAN",
"orion.primitives.tadgan.score_anomalies",
"orion.primitives.timeseries_anomalies.find_anomalies"
],
"init_params": {
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 21600,
"method": "mean"
@@ -21,7 +21,7 @@
1
]
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 100,
"target_size": 1
@@ -53,7 +53,7 @@
"orion.primitives.tadgan.TadGAN#1": {
"y": "y_hat"
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"index": "X_index",
"target_index": "y_index"
}
diff --git a/orion/pipelines/verified/tadgan/tadgan_without_dropout_gpu.json b/orion/pipelines/verified/tadgan/tadgan_without_dropout_gpu.json
index 0fee60a0..e956b464 100644
--- a/orion/pipelines/verified/tadgan/tadgan_without_dropout_gpu.json
+++ b/orion/pipelines/verified/tadgan/tadgan_without_dropout_gpu.json
@@ -1,16 +1,16 @@
{
"primitives": [
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate",
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate",
"sklearn.impute.SimpleImputer",
"sklearn.preprocessing.MinMaxScaler",
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences",
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences",
"orion.primitives.timeseries_preprocessing.slice_array_by_dims",
"orion.primitives.tadgan.TadGAN",
"orion.primitives.tadgan.score_anomalies",
"orion.primitives.timeseries_anomalies.find_anomalies"
],
"init_params": {
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 21600,
"method": "mean"
@@ -21,7 +21,7 @@
1
]
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 100,
"target_size": 1
@@ -165,7 +165,7 @@
"orion.primitives.tadgan.TadGAN#1": {
"y": "y_hat"
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"index": "X_index",
"target_index": "y_index"
}
diff --git a/orion/pipelines/verified/tadgan/tadgan_yahooa1.json b/orion/pipelines/verified/tadgan/tadgan_yahooa1.json
index bae702ec..34bf4f2b 100644
--- a/orion/pipelines/verified/tadgan/tadgan_yahooa1.json
+++ b/orion/pipelines/verified/tadgan/tadgan_yahooa1.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 1,
"method": "mean"
diff --git a/orion/pipelines/verified/tadgan/tadgan_yahooa2.json b/orion/pipelines/verified/tadgan/tadgan_yahooa2.json
index 46e90a52..2a9a20f2 100644
--- a/orion/pipelines/verified/tadgan/tadgan_yahooa2.json
+++ b/orion/pipelines/verified/tadgan/tadgan_yahooa2.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 1,
"method": "mean"
diff --git a/orion/pipelines/verified/tadgan/tadgan_yahooa3.json b/orion/pipelines/verified/tadgan/tadgan_yahooa3.json
index 1435c127..3c917de8 100644
--- a/orion/pipelines/verified/tadgan/tadgan_yahooa3.json
+++ b/orion/pipelines/verified/tadgan/tadgan_yahooa3.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 1,
"method": "mean"
diff --git a/orion/pipelines/verified/tadgan/tadgan_yahooa4.json b/orion/pipelines/verified/tadgan/tadgan_yahooa4.json
index c47e3389..91ab401a 100644
--- a/orion/pipelines/verified/tadgan/tadgan_yahooa4.json
+++ b/orion/pipelines/verified/tadgan/tadgan_yahooa4.json
@@ -1,5 +1,5 @@
{
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 1,
"method": "mean"
diff --git a/orion/pipelines/sandbox/vae/vae.json b/orion/pipelines/verified/vae/vae.json
similarity index 76%
rename from orion/pipelines/sandbox/vae/vae.json
rename to orion/pipelines/verified/vae/vae.json
index 66411f6e..8ecd7d93 100644
--- a/orion/pipelines/sandbox/vae/vae.json
+++ b/orion/pipelines/verified/vae/vae.json
@@ -1,16 +1,16 @@
{
"primitives": [
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate",
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate",
"sklearn.impute.SimpleImputer",
"sklearn.preprocessing.MinMaxScaler",
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences",
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences",
"orion.primitives.timeseries_preprocessing.slice_array_by_dims",
"orion.primitives.vae.VAE",
"orion.primitives.timeseries_errors.reconstruction_errors",
"orion.primitives.timeseries_anomalies.find_anomalies"
],
"init_params": {
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 21600,
"method": "mean"
@@ -21,7 +21,7 @@
1
]
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 100,
"target_size": 1
@@ -44,7 +44,7 @@
"orion.primitives.vae.VAE#1": {
"y": "y_hat"
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"index": "X_index",
"target_index": "y_index"
}
diff --git a/orion/pipelines/verified/vae/vae_artificialwithanomaly.json b/orion/pipelines/verified/vae/vae_artificialwithanomaly.json
new file mode 100644
index 00000000..eebcc81d
--- /dev/null
+++ b/orion/pipelines/verified/vae/vae_artificialwithanomaly.json
@@ -0,0 +1,6 @@
+{
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "time_column": "timestamp",
+ "interval": 600
+ }
+}
diff --git a/orion/pipelines/verified/vae/vae_msl.json b/orion/pipelines/verified/vae/vae_msl.json
new file mode 100644
index 00000000..e4fe0c11
--- /dev/null
+++ b/orion/pipelines/verified/vae/vae_msl.json
@@ -0,0 +1,6 @@
+{
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "time_column": "timestamp",
+ "interval": 21600
+ }
+}
diff --git a/orion/pipelines/verified/vae/vae_realadexchange.json b/orion/pipelines/verified/vae/vae_realadexchange.json
new file mode 100644
index 00000000..6b8aac0a
--- /dev/null
+++ b/orion/pipelines/verified/vae/vae_realadexchange.json
@@ -0,0 +1,6 @@
+{
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "time_column": "timestamp",
+ "interval": 3600
+ }
+}
diff --git a/orion/pipelines/verified/vae/vae_realawscloudwatch.json b/orion/pipelines/verified/vae/vae_realawscloudwatch.json
new file mode 100644
index 00000000..eebcc81d
--- /dev/null
+++ b/orion/pipelines/verified/vae/vae_realawscloudwatch.json
@@ -0,0 +1,6 @@
+{
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "time_column": "timestamp",
+ "interval": 600
+ }
+}
diff --git a/orion/pipelines/verified/vae/vae_realtraffic.json b/orion/pipelines/verified/vae/vae_realtraffic.json
new file mode 100644
index 00000000..eebcc81d
--- /dev/null
+++ b/orion/pipelines/verified/vae/vae_realtraffic.json
@@ -0,0 +1,6 @@
+{
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "time_column": "timestamp",
+ "interval": 600
+ }
+}
diff --git a/orion/pipelines/verified/vae/vae_realtweets.json b/orion/pipelines/verified/vae/vae_realtweets.json
new file mode 100644
index 00000000..eebcc81d
--- /dev/null
+++ b/orion/pipelines/verified/vae/vae_realtweets.json
@@ -0,0 +1,6 @@
+{
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "time_column": "timestamp",
+ "interval": 600
+ }
+}
diff --git a/orion/pipelines/verified/vae/vae_smap.json b/orion/pipelines/verified/vae/vae_smap.json
new file mode 100644
index 00000000..e4fe0c11
--- /dev/null
+++ b/orion/pipelines/verified/vae/vae_smap.json
@@ -0,0 +1,6 @@
+{
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "time_column": "timestamp",
+ "interval": 21600
+ }
+}
diff --git a/orion/pipelines/sandbox/vae/vae_viz.json b/orion/pipelines/verified/vae/vae_viz.json
similarity index 80%
rename from orion/pipelines/sandbox/vae/vae_viz.json
rename to orion/pipelines/verified/vae/vae_viz.json
index 7be6c7f7..fd3760e3 100644
--- a/orion/pipelines/sandbox/vae/vae_viz.json
+++ b/orion/pipelines/verified/vae/vae_viz.json
@@ -1,16 +1,16 @@
{
"primitives": [
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate",
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate",
"sklearn.impute.SimpleImputer",
"sklearn.preprocessing.MinMaxScaler",
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences",
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences",
"orion.primitives.timeseries_preprocessing.slice_array_by_dims",
"orion.primitives.vae.VAE",
"orion.primitives.timeseries_errors.reconstruction_errors",
"orion.primitives.timeseries_anomalies.find_anomalies"
],
"init_params": {
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 21600,
"method": "mean"
@@ -21,7 +21,7 @@
1
]
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 100,
"target_size": 1
@@ -44,7 +44,7 @@
"orion.primitives.vae.VAE#1": {
"y": "y_hat"
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"index": "X_index",
"target_index": "y_index"
}
@@ -67,7 +67,7 @@
},
{
"name": "index",
- "variable": "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1.index"
+ "variable": "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1.index"
},
{
"name": "errors",
diff --git a/orion/pipelines/verified/vae/vae_yahooa1.json b/orion/pipelines/verified/vae/vae_yahooa1.json
new file mode 100644
index 00000000..0fdb0776
--- /dev/null
+++ b/orion/pipelines/verified/vae/vae_yahooa1.json
@@ -0,0 +1,6 @@
+{
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "time_column": "timestamp",
+ "interval": 1
+ }
+}
diff --git a/orion/pipelines/verified/vae/vae_yahooa2.json b/orion/pipelines/verified/vae/vae_yahooa2.json
new file mode 100644
index 00000000..0fdb0776
--- /dev/null
+++ b/orion/pipelines/verified/vae/vae_yahooa2.json
@@ -0,0 +1,6 @@
+{
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "time_column": "timestamp",
+ "interval": 1
+ }
+}
diff --git a/orion/pipelines/verified/vae/vae_yahooa3.json b/orion/pipelines/verified/vae/vae_yahooa3.json
new file mode 100644
index 00000000..0fdb0776
--- /dev/null
+++ b/orion/pipelines/verified/vae/vae_yahooa3.json
@@ -0,0 +1,6 @@
+{
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "time_column": "timestamp",
+ "interval": 1
+ }
+}
diff --git a/orion/pipelines/verified/vae/vae_yahooa4.json b/orion/pipelines/verified/vae/vae_yahooa4.json
new file mode 100644
index 00000000..0fdb0776
--- /dev/null
+++ b/orion/pipelines/verified/vae/vae_yahooa4.json
@@ -0,0 +1,6 @@
+{
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "time_column": "timestamp",
+ "interval": 1
+ }
+}
diff --git a/orion/primitives/aer.py b/orion/primitives/aer.py
index 5223e120..75d80566 100644
--- a/orion/primitives/aer.py
+++ b/orion/primitives/aer.py
@@ -4,7 +4,7 @@
import numpy as np
import tensorflow as tf
-from mlprimitives.utils import import_object
+from mlstars.utils import import_object
from numpy import ndarray
from sklearn.preprocessing import MinMaxScaler
from tensorflow.keras.layers import Input
diff --git a/orion/primitives/jsons/keras.Sequential.DenseSeq2Seq.json b/orion/primitives/jsons/keras.Sequential.DenseSeq2Seq.json
index 61be51c0..65d953c6 100644
--- a/orion/primitives/jsons/keras.Sequential.DenseSeq2Seq.json
+++ b/orion/primitives/jsons/keras.Sequential.DenseSeq2Seq.json
@@ -10,7 +10,7 @@
"subtype": "regressor"
},
"modalities": [],
- "primitive": "mlprimitives.adapters.keras.Sequential",
+ "primitive": "mlstars.adapters.keras.Sequential",
"fit": {
"method": "fit",
"args": [
diff --git a/orion/primitives/jsons/keras.Sequential.LSTMSeq2Seq.json b/orion/primitives/jsons/keras.Sequential.LSTMSeq2Seq.json
index 92519029..4925fd72 100644
--- a/orion/primitives/jsons/keras.Sequential.LSTMSeq2Seq.json
+++ b/orion/primitives/jsons/keras.Sequential.LSTMSeq2Seq.json
@@ -10,7 +10,7 @@
"subtype": "regressor"
},
"modalities": [],
- "primitive": "mlprimitives.adapters.keras.Sequential",
+ "primitive": "mlstars.adapters.keras.Sequential",
"fit": {
"method": "fit",
"args": [
diff --git a/orion/primitives/tadgan.py b/orion/primitives/tadgan.py
index 6d8282da..5f3d9d14 100644
--- a/orion/primitives/tadgan.py
+++ b/orion/primitives/tadgan.py
@@ -8,7 +8,7 @@
import numpy as np
import pandas as pd
import tensorflow as tf
-from mlprimitives.utils import import_object
+from mlstars.utils import import_object
from numpy import ndarray
from scipy import stats
from tensorflow.keras import Model
diff --git a/orion/primitives/timeseries_anomalies.py b/orion/primitives/timeseries_anomalies.py
index fb9390a2..da315d2c 100644
--- a/orion/primitives/timeseries_anomalies.py
+++ b/orion/primitives/timeseries_anomalies.py
@@ -137,6 +137,7 @@ def _find_threshold(errors, z_range):
z, cost = best[0:2]
if cost < best_cost:
best_z = z[0]
+ best_cost = cost
return mean + best_z * std
diff --git a/orion/primitives/timeseries_errors.py b/orion/primitives/timeseries_errors.py
index f304b5ba..4fde3863 100644
--- a/orion/primitives/timeseries_errors.py
+++ b/orion/primitives/timeseries_errors.py
@@ -43,7 +43,7 @@ def regression_errors(y, y_hat, smoothing_window=0.01, smooth=True,
if not smooth:
return errors
- smoothing_window = max(1, int(len(y)*smoothing_window))
+ smoothing_window = max(1, int(len(y) * smoothing_window))
errors = pd.Series(errors).ewm(span=smoothing_window).mean().values
if mask:
diff --git a/orion/primitives/vae.py b/orion/primitives/vae.py
index b350a768..947dcee8 100644
--- a/orion/primitives/vae.py
+++ b/orion/primitives/vae.py
@@ -11,7 +11,7 @@
import numpy as np
import tensorflow as tf
-from mlprimitives.utils import import_object
+from mlstars.utils import import_object
from tensorflow.keras import backend as K
from tensorflow.keras.layers import Input
from tensorflow.keras.models import Model
diff --git a/setup.cfg b/setup.cfg
index 37883dda..2e4e8c80 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -1,5 +1,5 @@
[bumpversion]
-current_version = 0.4.1
+current_version = 0.5.0.dev0
commit = True
tag = True
parse = (?P\d+)\.(?P\d+)\.(?P\d+)(\.(?P[a-z]+)(?P\d+))?
diff --git a/setup.py b/setup.py
index 68727bff..33c7a7bb 100644
--- a/setup.py
+++ b/setup.py
@@ -21,7 +21,7 @@
"tensorflow>=2.2,<2.5;python_version>='3.8'",
's3fs>=0.2.2,<0.5',
'mlblocks>=0.4.1,<0.5',
- 'mlprimitives>=0.3.2,<0.4',
+ 'ml-stars>=0.1.1,<0.2',
'numpy>=1.17.4,<1.19',
'pandas>=1,<2',
'scikit-learn>=0.22,<1.2',
@@ -29,11 +29,15 @@
'numba>=0.48,<0.52',
'pyts>=0.9,<0.11',
'azure-cognitiveservices-anomalydetector>=0.3,<0.4',
- 'xlsxwriter>=1.3.6<1.4',
+ 'xlsxwriter>=1.3.6,<1.4',
+ 'tqdm>=4.36.1',
# fix conflict
'h5py<2.11.0,>=2.10.0',
'protobuf<4',
+
+ # fails on python 3.6
+ 'opencv-python<4.7',
]
setup_requires = [
@@ -122,6 +126,6 @@
test_suite='tests',
tests_require=tests_require,
url='https://github.com/sintel-dev/Orion',
- version='0.4.1',
+ version='0.5.0.dev0',
zip_safe=False,
)
diff --git a/tests/primitives/test_timeseries_anomalies.py b/tests/primitives/test_timeseries_anomalies.py
index 67ce748d..469d7460 100644
--- a/tests/primitives/test_timeseries_anomalies.py
+++ b/tests/primitives/test_timeseries_anomalies.py
@@ -203,29 +203,29 @@ def test_find_anomalies_no_anomalies(self):
self._run([0, 0, 0, 0], np.array([]))
def test_find_anomalies_one_anomaly(self):
- self._run([0, 0.5, 0.5, 0], np.array([[1., 4., 0.025]]))
+ self._run([0, 0.5, 0.5, 0], np.array([[1., 4., 0.5]]))
def test_find_anomalies_open_start(self):
- self._run([0.5, 0.5, 0, 0], np.array([[1., 3., 0.025]]))
+ self._run([0.5, 0.5, 0, 0], np.array([[1., 3., 0.5]]))
def test_find_anomalies_open_end(self):
- self._run([0, 0, 0.5, 0.5], np.array([[2., 4., 0.025]]))
+ self._run([0, 0, 0.5, 0.5], np.array([[2., 4., 0.5]]))
def test_find_anomalies_two_anomalies(self):
- self._run([0.5, 0, 0.5, 0], np.array([[1., 4., 0.025]]))
- self._run([0, 0.5, 0, 0.5], np.array([[1., 4., 0.025]]))
+ self._run([0.5, 0, 0.5, 0], np.array([[1., 4., 0.5]]))
+ self._run([0, 0.5, 0, 0.5], np.array([[1., 4., 0.5]]))
def test_find_anomalies_multiple_non_overlapping_thresholds(self):
self._run([0, 0, 0.5, 0.5, 0, 0, 0.5, 0.5, 0, 0],
- np.array([[2., 4., 0.025], [6., 8., 0.025]]), index=self.INDEX_LONG,
+ np.array([[2., 4., 0.5], [6., 8., 0.5]]), index=self.INDEX_LONG,
window_size=4, window_step_size=4)
def test_find_anomalies_multiple_overlapping_thresholds(self):
- self._run([0, 0, 0.5, 0.5, 0, 0, 0.5, 0.5, 0, 0], np.array([[2., 9., 0.025]]),
+ self._run([0, 0, 0.5, 0.5, 0, 0, 0.5, 0.5, 0, 0], np.array([[2., 9., 0.5]]),
index=self.INDEX_LONG, window_size=4, window_step_size=2)
def test_find_anomalies_lower_threshold(self):
- self._run([0.5, 0.5, 0, 0], np.array([[1., 4., 0.025]]), lower_threshold=True)
+ self._run([0.5, 0.5, 0, 0], np.array([[1., 4., 0.5]]), lower_threshold=True)
def test_find_anomalies_fixed_threshold(self):
self._run([0.5, 0.5, 0, 0], np.array([]), fixed_threshold=True)
diff --git a/tests/requirement_files/latest_requirements.txt b/tests/requirement_files/latest_requirements.txt
index b9fbb91f..0d715b82 100644
--- a/tests/requirement_files/latest_requirements.txt
+++ b/tests/requirement_files/latest_requirements.txt
@@ -1,35 +1,34 @@
-absl-py==1.3.0
+absl-py==1.4.0
astunparse==1.6.3
-attrs==22.2.0
azure-cognitiveservices-anomalydetector==0.3.0
azure-common==1.1.28
-azure-core==1.26.1
-beautifulsoup4==4.11.1
-botocore==1.29.37
-cachetools==5.2.0
+azure-core==1.26.4
+beautifulsoup4==4.12.2
+botocore==1.29.109
+cachetools==5.3.0
certifi==2022.12.7
-charset-normalizer==2.1.1
+charset-normalizer==3.1.0
click==7.1.2
-cloudpickle==2.2.0
-coverage==7.0.1
+cloudpickle==2.2.1
+coverage==7.2.3
dask==2022.2.0
distributed==2022.2.0
-exceptiongroup==1.1.0
+exceptiongroup==1.1.1
featuretools==0.22.0
-fsspec==2022.11.0
+fsspec==2023.1.0
gast==0.3.3
-google-auth==2.15.0
+google-auth==2.17.2
google-auth-oauthlib==0.4.6
google-pasta==0.2.0
graphviz==0.20.1
-grpcio==1.51.1
+grpcio==1.53.0
h5py==2.10.0
HeapDict==1.0.1
idna==3.4
-imageio==2.23.0
-importlib-metadata==5.2.0
-iniconfig==1.1.1
-invoke==1.7.3
+imageio==2.27.0
+importlib-metadata==6.2.1
+iniconfig==2.0.0
+invoke==2.0.0
iso639==0.1.4
isodate==0.6.1
Jinja2==3.1.2
@@ -38,46 +37,46 @@ joblib==1.2.0
Keras==2.4.3
Keras-Preprocessing==1.1.2
langdetect==1.0.9
-lightfm==1.16
+lightfm==1.17
llvmlite==0.34.0
locket==1.0.0
Markdown==2.6.11
markdown-rundoc==0.3.1
-MarkupSafe==2.1.1
+MarkupSafe==2.1.2
mlblocks==0.4.1
-mlprimitives==0.3.2
-msgpack==1.0.4
+mlprimitives==0.3.4
+msgpack==1.0.5
msrest==0.7.1
networkx==2.6.3
-nltk==3.8
+nltk==3.8.1
numba==0.51.2
numpy==1.18.5
oauthlib==3.2.2
opencv-python==4.6.0.66
opt-einsum==3.3.0
-orion-ml==0.4.1.dev0
-packaging==22.0
+orion-ml==0.4.2.dev0
+packaging==23.0
pandas==1.3.5
partd==1.3.0
patsy==0.5.3
-Pillow==9.3.0
+Pillow==9.5.0
pluggy==1.0.0
-prompt-toolkit==3.0.36
+prompt-toolkit==3.0.38
protobuf==3.20.3
psutil==5.9.4
pyasn1==0.4.8
pyasn1-modules==0.2.8
-Pygments==2.13.0
-pytest==7.2.0
+Pygments==2.14.0
+pytest==7.3.0
pytest-cov==4.0.0
python-dateutil==2.8.2
python-louvain==0.13
pyts==0.10.0
-pytz==2022.7
+pytz==2023.3
PyWavelets==1.3.0
PyYAML==6.0
regex==2022.10.31
-requests==2.28.1
+requests==2.28.2
requests-oauthlib==1.3.1
rsa==4.9
rundoc==0.4.5
@@ -87,28 +86,28 @@ scikit-learn==1.0.2
scipy==1.7.3
six==1.16.0
sortedcontainers==2.4.0
-soupsieve==2.3.2.post1
+soupsieve==2.4
statsmodels==0.12.2
tabulate==0.8.10
tblib==1.7.0
-tensorboard==2.11.0
+tensorboard==2.11.2
tensorboard-data-server==0.6.1
tensorboard-plugin-wit==1.8.1
tensorflow==2.3.4
tensorflow-estimator==2.3.0
-termcolor==2.1.1
+termcolor==2.2.0
threadpoolctl==3.1.0
tifffile==2021.11.2
tomli==2.0.1
toolz==0.12.0
tornado==6.2
-tqdm==4.64.1
-typing_extensions==4.4.0
-urllib3==1.26.13
-wcwidth==0.2.5
-Werkzeug==2.2.2
-wrapt==1.14.1
+tqdm==4.65.0
+typing_extensions==4.5.0
+urllib3==1.26.15
+wcwidth==0.2.6
+Werkzeug==2.2.3
+wrapt==1.15.0
xgboost==0.90
-XlsxWriter==3.0.3
+XlsxWriter==1.3.9
zict==2.2.0
-zipp==3.11.0
+zipp==3.15.0
diff --git a/tests/test_analysis.py b/tests/test_analysis.py
index 66b2743a..0668f221 100644
--- a/tests/test_analysis.py
+++ b/tests/test_analysis.py
@@ -9,11 +9,11 @@
@pytest.fixture
def tadgan_hyperparameters():
return {
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"interval": 1,
"time_column": "timestamp",
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 100,
"target_size": 1
diff --git a/tests/test_data.py b/tests/test_data.py
index 6e23539b..77814edb 100644
--- a/tests/test_data.py
+++ b/tests/test_data.py
@@ -49,7 +49,7 @@ def test_download_new(exists_mock, read_csv_mock):
# assert
assert returned == read_csv_mock.return_value
- expected_url = 'https://d3-ai-orion.s3.amazonaws.com/a_signal_name.csv'
+ expected_url = 'https://sintel-orion.s3.amazonaws.com/a_signal_name.csv'
read_csv_mock.assert_called_once_with(expected_url)
expected_filename = os.path.join(DATA_PATH, 'a_signal_name.csv')
diff --git a/tutorials/Multivariate_Input.ipynb b/tutorials/Multivariate_Input.ipynb
index 37e5a2d0..75d6c5ed 100644
--- a/tutorials/Multivariate_Input.ipynb
+++ b/tutorials/Multivariate_Input.ipynb
@@ -286,7 +286,7 @@
"from orion import Orion\n",
"\n",
"hyperparameters = {\n",
- " \"mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1\": {\n",
+ " \"mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1\": {\n",
" 'target_column': 0 \n",
" },\n",
" 'keras.Sequential.LSTMTimeSeriesRegressor#1': {\n",
@@ -381,7 +381,7 @@
"\n",
"```python3\n",
"hyperparameters = {\n",
- " \"mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1\": {\n",
+ " \"mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1\": {\n",
" 'window_size': 100,\n",
" 'target_column': 0 \n",
" },\n",
@@ -429,7 +429,7 @@
],
"source": [
"hyperparameters = {\n",
- " \"mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1\": {\n",
+ " \"mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1\": {\n",
" 'window_size': 150,\n",
" 'target_column': 0 \n",
" },\n",
@@ -470,7 +470,7 @@
],
"metadata": {
"kernelspec": {
- "display_name": "Python 3",
+ "display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
@@ -484,7 +484,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.6.10"
+ "version": "3.8.16"
}
},
"nbformat": 4,
diff --git a/tutorials/pipelines/azure.ipynb b/tutorials/pipelines/azure.ipynb
index a6319789..48d86ffe 100644
--- a/tutorials/pipelines/azure.ipynb
+++ b/tutorials/pipelines/azure.ipynb
@@ -141,7 +141,7 @@
"outputs": [],
"source": [
"hyperparameters = {\n",
- " \"mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1\": {\n",
+ " \"mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1\": {\n",
" \"interval\": 21600,\n",
" },\n",
" \"orion.primitives.azure_anomaly_detector.split_sequence#1\": {\n",
@@ -201,7 +201,7 @@
],
"metadata": {
"kernelspec": {
- "display_name": "Python 3",
+ "display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
@@ -215,7 +215,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.7.11"
+ "version": "3.8.16"
}
},
"nbformat": 4,
diff --git a/tutorials/pipelines/lstm_dynamic_threshold.ipynb b/tutorials/pipelines/lstm_dynamic_threshold.ipynb
index 341a9374..a036af00 100644
--- a/tutorials/pipelines/lstm_dynamic_threshold.ipynb
+++ b/tutorials/pipelines/lstm_dynamic_threshold.ipynb
@@ -116,15 +116,7 @@
"execution_count": 3,
"id": "fa524c4c",
"metadata": {},
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "Using TensorFlow backend.\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"from mlblocks import MLPipeline\n",
"\n",
@@ -171,10 +163,10 @@
{
"data": {
"text/plain": [
- "['mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate',\n",
+ "['mlstars.custom.timeseries_preprocessing.time_segments_aggregate',\n",
" 'sklearn.impute.SimpleImputer',\n",
" 'sklearn.preprocessing.MinMaxScaler',\n",
- " 'mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences',\n",
+ " 'mlstars.custom.timeseries_preprocessing.rolling_window_sequences',\n",
" 'keras.Sequential.LSTMTimeSeriesRegressor',\n",
" 'orion.primitives.timeseries_errors.regression_errors',\n",
" 'orion.primitives.timeseries_anomalies.find_anomalies']"
@@ -665,7 +657,7 @@
],
"metadata": {
"kernelspec": {
- "display_name": "Python 3",
+ "display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
@@ -679,7 +671,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.7.11"
+ "version": "3.8.16"
}
},
"nbformat": 4,
diff --git a/tutorials/tulog/Tulog.ipynb b/tutorials/tulog/Tulog.ipynb
index 1b74b94b..e11b45aa 100644
--- a/tutorials/tulog/Tulog.ipynb
+++ b/tutorials/tulog/Tulog.ipynb
@@ -329,10 +329,10 @@
"\n",
"```\n",
"\"primitives\": [ \n",
- " \"mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate”,\n",
+ " \"mlstars.custom.timeseries_preprocessing.time_segments_aggregate”,\n",
" \"sklearn.impute.SimpleImputer\",\n",
" \"sklearn.preprocessing.MinMaxScaler\",\n",
- " \"mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences\",\n",
+ " \"mlstars.custom.timeseries_preprocessing.rolling_window_sequences\",\n",
" \"orion.primitives.tadgan.TadGAN\",\n",
" \"orion.primitives.tadgan.score_anomalies\",\n",
" \"orion.primitives.timeseries_anomalies.find_anomalies\"\n",
@@ -1025,7 +1025,7 @@
"from orion import Orion\n",
"\n",
"hyperparameters = {\n",
- " \"mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1\": {\n",
+ " \"mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1\": {\n",
" \"interval\": 3600 # hour level\n",
" },\n",
" 'orion.primitives.tadgan.TadGAN#1': {\n",
@@ -1346,7 +1346,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.13"
+ "version": "3.8.16"
}
},
"nbformat": 4,
diff --git a/tutorials/tulog/model.py b/tutorials/tulog/model.py
index 0dafdfa3..1d4b0ba5 100644
--- a/tutorials/tulog/model.py
+++ b/tutorials/tulog/model.py
@@ -2,15 +2,15 @@
encoder = [
{
- "class": "keras.layers.Bidirectional",
+ "class": "tensorflow.keras.layers.LSTM",
"parameters": {
- "layer": {
- "class": "keras.layers.LSTM",
- "parameters": {
- "units": 100,
- "return_sequences": True
- }
- }
+ "units": 100,
+ "return_sequences": True,
+ "activation": "tanh",
+ "recurrent_activation": "sigmoid",
+ "use_bias": True,
+ "recurrent_dropout": 0.0,
+ "unroll": False
}
},
{
@@ -49,15 +49,19 @@
}
},
{
- "class": "keras.layers.Bidirectional",
+ "class": "tensorflow.keras.layers.Bidirectional",
"parameters": {
"layer": {
- "class": "keras.layers.LSTM",
+ "class": "tensorflow.keras.layers.LSTM",
"parameters": {
"units": 64,
"return_sequences": True,
"dropout": 0.2,
- "recurrent_dropout": 0.2
+ "activation": "tanh",
+ "recurrent_activation": "sigmoid",
+ "use_bias": True,
+ "recurrent_dropout": 0.0,
+ "unroll": False
}
},
"merge_mode": "concat"
@@ -70,15 +74,19 @@
}
},
{
- "class": "keras.layers.Bidirectional",
+ "class": "tensorflow.keras.layers.Bidirectional",
"parameters": {
"layer": {
- "class": "keras.layers.LSTM",
- "parameters": {
- "units": 64,
- "return_sequences": True,
- "dropout": 0.2,
- "recurrent_dropout": 0.2
+ "class": "tensorflow.keras.layers.LSTM",
+ "parameters": {
+ "units": 64,
+ "return_sequences": True,
+ "dropout": 0.2,
+ "activation": "tanh",
+ "recurrent_activation": "sigmoid",
+ "use_bias": True,
+ "recurrent_dropout": 0.0,
+ "unroll": True
}
},
"merge_mode": "concat"
@@ -112,7 +120,7 @@
}
},
{
- "class": "keras.layers.advanced_activations.LeakyReLU",
+ "class": "keras.layers.LeakyReLU",
"parameters": {
"alpha": 0.2
}
@@ -131,7 +139,7 @@
}
},
{
- "class": "keras.layers.advanced_activations.LeakyReLU",
+ "class": "keras.layers.LeakyReLU",
"parameters": {
"alpha": 0.2
}
@@ -150,7 +158,7 @@
}
},
{
- "class": "keras.layers.advanced_activations.LeakyReLU",
+ "class": "keras.layers.LeakyReLU",
"parameters": {
"alpha": 0.2
}
@@ -169,7 +177,7 @@
}
},
{
- "class": "keras.layers.advanced_activations.LeakyReLU",
+ "class": "keras.layers.LeakyReLU",
"parameters": {
"alpha": 0.2
}
@@ -204,7 +212,7 @@
}
},
{
- "class": "keras.layers.advanced_activations.LeakyReLU",
+ "class": "keras.layers.LeakyReLU",
"parameters": {
"alpha": 0.2
}
@@ -222,7 +230,7 @@
}
},
{
- "class": "keras.layers.advanced_activations.LeakyReLU",
+ "class": "keras.layers.LeakyReLU",
"parameters": {
"alpha": 0.2
}
@@ -257,4 +265,4 @@
"layers_generator": generator,
"layers_critic_x": criticX,
"layers_critic_z": criticZ
-}
\ No newline at end of file
+}
diff --git a/tutorials/tulog/tadgan.json b/tutorials/tulog/tadgan.json
index a767e691..f3fcd4b8 100644
--- a/tutorials/tulog/tadgan.json
+++ b/tutorials/tulog/tadgan.json
@@ -1,18 +1,18 @@
{
"primitives": [
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate",
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate",
"sklearn.impute.SimpleImputer",
"sklearn.preprocessing.MinMaxScaler",
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences",
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences",
"orion.primitives.timeseries_preprocessing.slice_array_by_dims",
"orion.primitives.tadgan.TadGAN",
"orion.primitives.tadgan.score_anomalies",
"orion.primitives.timeseries_anomalies.find_anomalies"
],
"init_params": {
- "mlprimitives.custom.timeseries_preprocessing.time_segments_aggregate#1": {
+ "mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
- "interval": 1800,
+ "interval": 21600,
"method": "mean"
},
"sklearn.preprocessing.MinMaxScaler#1": {
@@ -21,7 +21,7 @@
1
]
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 100,
"target_size": 1
@@ -31,11 +31,124 @@
"axis": 2
},
"orion.primitives.tadgan.TadGAN#1": {
- "epochs": 5
+ "epochs": 5,
+ "layers_encoder": [
+ {
+ "class": "tensorflow.keras.layers.Bidirectional",
+ "parameters": {
+ "layer": {
+ "class": "tensorflow.keras.layers.LSTM",
+ "parameters": {
+ "units": "lstm_units",
+ "return_sequences": true,
+ "activation": "tanh",
+ "recurrent_activation": "sigmoid",
+ "use_bias": true,
+ "recurrent_dropout": 0.0,
+ "unroll": false
+ }
+ }
+ }
+ },
+ {
+ "class": "tensorflow.keras.layers.Flatten",
+ "parameters": {}
+ },
+ {
+ "class": "tensorflow.keras.layers.Dense",
+ "parameters": {
+ "units": "dense_units"
+ }
+ },
+ {
+ "class": "tensorflow.keras.layers.Reshape",
+ "parameters": {
+ "target_shape": "encoder_reshape_shape"
+ }
+ }
+ ],
+ "layers_generator": [
+ {
+ "class": "tensorflow.keras.layers.Flatten",
+ "parameters": {}
+ },
+ {
+ "class": "tensorflow.keras.layers.Dense",
+ "parameters": {
+ "units": "generator_reshape_dim"
+ }
+ },
+ {
+ "class": "tensorflow.keras.layers.Reshape",
+ "parameters": {
+ "target_shape": "generator_reshape_shape"
+ }
+ },
+ {
+ "class": "tensorflow.keras.layers.Bidirectional",
+ "parameters": {
+ "layer": {
+ "class": "tensorflow.keras.layers.LSTM",
+ "parameters": {
+ "units": 64,
+ "return_sequences": true,
+ "dropout": 0.2,
+ "activation": "tanh",
+ "recurrent_activation": "sigmoid",
+ "use_bias": true,
+ "recurrent_dropout": 0.0,
+ "unroll": false
+ }
+ },
+ "merge_mode": "concat"
+ }
+ },
+ {
+ "class": "tensorflow.keras.layers.UpSampling1D",
+ "parameters": {
+ "size": 2
+ }
+ },
+ {
+ "class": "tensorflow.keras.layers.Bidirectional",
+ "parameters": {
+ "layer": {
+ "class": "tensorflow.keras.layers.LSTM",
+ "parameters": {
+ "units": 64,
+ "return_sequences": true,
+ "dropout": 0.2,
+ "activation": "tanh",
+ "recurrent_activation": "sigmoid",
+ "use_bias": true,
+ "recurrent_dropout": 0.0,
+ "unroll": false
+ }
+ },
+ "merge_mode": "concat"
+ }
+ },
+ {
+ "class": "tensorflow.keras.layers.TimeDistributed",
+ "parameters": {
+ "layer": {
+ "class": "tensorflow.keras.layers.Dense",
+ "parameters": {
+ "units": 1
+ }
+ }
+ }
+ },
+ {
+ "class": "tensorflow.keras.layers.Activation",
+ "parameters": {
+ "activation": "tanh"
+ }
+ }
+ ]
},
"orion.primitives.tadgan.score_anomalies#1": {
- "error_smooth_window": 200,
- "critic_smooth_window": 200
+ "rec_error_type": "dtw"
},
"orion.primitives.timeseries_anomalies.find_anomalies#1": {
"window_size_portion": 0.33,
@@ -52,31 +165,9 @@
"orion.primitives.tadgan.TadGAN#1": {
"y": "y_hat"
},
- "mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences#1": {
+ "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"index": "X_index",
"target_index": "y_index"
}
- },
- "outputs": {
- "default": [
- {
- "name": "events",
- "variable": "orion.primitives.timeseries_anomalies.find_anomalies#1.y"
- }
- ],
- "visualization": [
- {
- "name": "X",
- "variable": "sklearn.preprocessing.MinMaxScaler#1.X"
- },
- {
- "name": "X_hat",
- "variable": "orion.primitives.tadgan.TadGAN#1.y_hat"
- },
- {
- "name": "es",
- "variable": "orion.primitives.tadgan.score_anomalies#1.errors"
- }
- ]
}
-}
+}
\ No newline at end of file