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Claim an sklearn algorithm to implement and troubleshoot #27
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Tagging everyone who said they were interested in contributing to the machine learning part of the project in the introduction thread: @htcai, @loucru1 @bmcgeehan @Umeshiso @swbiggs4 @danrieman @rramyr @Inquisitive-Geek @brankaj @yl565 @Ramaa-Nathan @ejsegall @FadiAlnabolsi @sameertipnis @VijYadav @ctipnis. Update: also tagging @yigalron. |
Thanks for the sample notebook! I would like to implement Linear SVM with regularization. |
@htcai awesome. Can you specify which sklearn function(s) you plan to use for the model? |
Thanks for setting this up. I would like to try LASSO, implementation sklearn.linear_model.LassoCV. |
I plan to implement the Nearest Neighbors Classification |
@yigalron did you want to claim |
I'm planning to start with the KNeighborsClassifier |
I plan to test Decision Tree CART (sklearn.tree.DecisionTreeClassifier) algorithm |
Hi Daniel, |
@VijYadav, you'll have to create the directory, since it currently doesn't exist. I'll submit a pull request as an example. |
when trying to set up the conda environment on windows (conda env create --quiet --force --file environment.yml) I get an error: yaml.scanner.ScannerError: mapping values are not allowed here any ideas what I did wrong? |
OK; anyway it seems to have been a user error; I'm trying again |
* Create a template and directory for algorithm See #27 * Add notebook nomenclature example
Hi all, I will claim AdaBoost. |
Hey Folks - I will give RandomForestClassifier a shot. Mans |
I have an initial version of the K-Nearest neighbor algorithm, and I issued a pull request; not sure if it got into the master. |
I would like to claim spectral clustering, and give it a try |
I would like to work on the multi-layer perceptron classifier. sklearn.neural_network.MLPClassifier |
I'd like to claim LDA/QDA and give it a shot |
I'll also take a look at the Passive Aggressive Classifier |
In the August 26 meetup, we discussed having each team member in the machine learning group claim an algorithm. We've made lot's of progress on the example notebook (
1.TCGA-MLexample.ipynb
) since then (see #18 & #25). Currently,1.TCGA-MLexample.ipynb
uses elastic net logistic regression implemented inSGDClassifier
.The goal of this repository is for people to:
1.TCGA-MLexample.ipynb
in analgorithms
directory. So if I took the SVM classifier, I would copy1.TCGA-MLexample.ipynb
toalgorithms/SVC-dhimmel.ipynb
. Then I would make my edits toalgorithms/SVC-dhimmel.ipynb
to switch to an SVC classifier.Best of luck! If you can work on this before the August 9 meetup then great! Otherwise make sure to bring a laptop with the
cognoma-machine-learning
environment installed.The text was updated successfully, but these errors were encountered: