search.json

[{"draft":false,"title":"Dask all Folks: preparing large datasets","tags":["dask","development"],"author":"Noah Novšak","longExcerpt":"Preparing large HDF5 datasets that load into Orange as on-disk data. This post outlines the specifics of the HDF5 format used by Orange and provides Python code that will help you prepare your own large datasets.","shortExcerpt":"Preparing large HDF5 datasets that load into Orange as on-disk data.","url":"dask-all-folks-preparing-large-datasets","_type":"blog"},{"draft":false,"title":"Recap of 26th International Conference on Discovery Science","tags":["conference","research"],"author":"Martin Špendl","longExcerpt":"Two of our PhD students presented their work on the 26th International Conference on Discovery Science in Porto.","shortExcerpt":"Highlighting our papers from the International Conference on Discovery Science","url":"recap-of-26th-international-conference-on-discovery-science","_type":"blog"},{"draft":false,"title":"Fall Season Brings Fresh Content to the Introduction to Data Science Series","tags":["update","video series"],"author":"Erika Funa","longExcerpt":"Updates in the Introduction to Data Science Video Series, new video logistic regression nomogram.","shortExcerpt":"Updates in the Introduction to Data Science Video Series, new video logistic regression nomogram.","url":"fall-season-brings-fresh-content-to-the-introduction-to-data-science-series","_type":"blog"},{"draft":false,"title":"Why Removing Features Isn't Enough","tags":["fairness"],"author":"Žan Mervič","longExcerpt":"In this blog, we confront the common misconception that merely removing a protected attribute from a dataset eliminates bias in model predictions. Our case study reveals that models trained without these attributes still produce biased results. This is due to feature correlations that indirectly capture the protected information. Our conclusion? You cannot sidestep the need for specialized fairness algorithms.","shortExcerpt":"Find out why merely removing protected attributes will not fix bias. Features often correlate, letting models infer biases. Fairness algorithms are key for genuine bias mitigation.","url":"why-removing-features-isnt-enough","_type":"blog"},{"draft":false,"title":"Orange Fairness - Reweighing as a preprocessor","tags":["fairness","reweighing"],"author":"Žan Mervič","longExcerpt":"Diving deeper into the Orange fairness Reweighing widget, we explore its use as a preprocessor for models. Discover the new widgets and fairness scoring metrics; all illustrated using the German credit dataset, supplemented with visual insights through box plots.","shortExcerpt":"Expanding on the Orange fairness Reweighing widget: using it as a preprocessor and integrating new fairness scoring metrics.","url":"orange-fairness-reweighing-as-a-preprocessor","_type":"blog"},{"draft":false,"title":"Orange Fairness - Reweighing a Dataset","tags":["fairness","reweighing"],"author":"Žan Mervič","longExcerpt":"Building on our exploration of the Orange fairness addon, this blog delves into the Reweighing widget. By adjusting weights for dataset instances, the widget addresses bias, focusing on underrepresented groups. Using the Compas dataset as an example, we demonstrate how bias decreases post-reweighting, presenting visual insights into the distribution of adjusted weights and their impact on dataset fairness.","shortExcerpt":"Introducing the Reweighing widget in Orange, a solution for dataset bias mitigation.","url":"orange-fairness-reweighing-a-dataset","_type":"blog"},{"draft":false,"title":"Orange Fairness - Equal Odds Postprocessing","tags":["fairness","equal odds postprocessing"],"author":"Žan Mervič","longExcerpt":"In this blog, we delve into the Equal Odds Postprocessing widget, a tool designed to enhance fairness in machine learning models. We break down how the algorithm works by modifying predictions to meet Equalized Odds criteria. Using a real-world example with the German credit dataset, we demonstrate its efficacy in improving fairness metrics while marginally affecting accuracy.","shortExcerpt":"Explore the Equal Odds Postprocessing widget in Orange, designed to fine-tune your model's fairness. We explain how the algorithm operates and showcase its effectiveness with an example using the German credit dataset.","url":"orange-fairness-equal-odds-postprocessing","_type":"blog"},{"draft":false,"title":"Orange Fairness - Adversarial Debiasing","tags":["fairness","adversarial debiasing"],"author":"Žan Mervič","longExcerpt":"This blog post focuses on the Adversarial Debiasing model in Orange, a tool for enhancing fairness in your machine learning algorithms. We will walk through how to use it and explain the trade-offs that come with using fairness algorithms.","shortExcerpt":"Learn how to use the Adversarial Debiasing model in Orange for fairer machine learning.","url":"orange-fairness-adversarial-debiasing","_type":"blog"},{"draft":false,"title":"Orange Fairness - Dataset Bias","tags":["fairness","dataset bias"],"author":"Žan Mervič","longExcerpt":"In an era where AI drives decisions impacting real lives, fairness in machine learning is paramount. Take the `Adult` dataset, which shows discrepancies in salary predictions based on gender. Addressing such concerns, Orange introduces a fairness add-on. Using new widgets, users can identify and mitigate biases in their datasets or model predictions.","shortExcerpt":"Orange now supports methods for detecting and mitigating bias in machine learning.","url":"orange-fairness-dataset-bias","_type":"blog"},{"draft":false,"title":"A dash of Dask","tags":["dask","development"],"author":"Noah Novšak","longExcerpt":"Updates in the dask project, integrating machine learning methods and enhancing efficiency in a data preprocessor.","shortExcerpt":"Updates in the dask project, integrating machine learning methods and enhancing efficiency in a data preprocessor.","url":"a-dash-of-dask","_type":"blog"},{"draft":false,"title":"Pumice challenge","tags":["education"],"author":"Anja Mejač, Janez Demšar","longExcerpt":"One thousand Slovenian students took part in a data mining challenge","shortExcerpt":"One thousand Slovenian students took part in a data mining challenge","url":"pumice-challenge","_type":"blog"},{"draft":false,"title":"Živjo, Orange!","tags":["gui"],"author":"Janez Demšar","longExcerpt":"Orange speaks Slovenian!","shortExcerpt":"Orange speaks Slovenian!","url":"zivjo-orange","_type":"blog"},{"draft":false,"title":"Interval Sliders","tags":["development"],"author":"Janez Demšar","longExcerpt":"What does it take to add a second handle to a slider.","shortExcerpt":"What does it take to add a second handle to a slider.","url":"interval-sliders","_type":"blog"},{"draft":false,"title":"Single-sample GSEA is now in Orange","tags":["bioinformatics"],"author":"Martin Špendl","longExcerpt":"Single-sample extension of Gene Set Enrichment Analysis now in Bioinformatics add-on.","shortExcerpt":"Single-sample extension of Gene Set Enrichment Analysis now in Bioinformatics add-on.","url":"single-sample-gsea-is-now-in-orange","_type":"blog"},{"draft":false,"title":"Cox regression in Orange","tags":["survival analysis","cox regression"],"author":"Jaka Kokošar","longExcerpt":"Orange built-in methods for testing and scoring the predictive models now support survival-related models like Cox regression.","shortExcerpt":"Orange built-in methods for testing and scoring the predictive models now support survival-related models like Cox regression.","url":"cox-regression-in-orange","_type":"blog"},{"draft":false,"title":"Meet Trubar, a friend of Orange","tags":["development"],"author":"Janez Demšar","longExcerpt":"A new, general utility for localization of Python software, developed for Orange","shortExcerpt":"A new, general utility for localization of Python software","url":"meet-trubar-a-friend-of-orange","_type":"blog"},{"draft":false,"title":"Orange you going to ask about dask?","tags":["dask","widgets"],"author":"Noah Novšak","longExcerpt":"What we are doing to improve Orange's data processing abilities, how we can tackle the huge amounts of data already available today, and what role dask plays in all this.","shortExcerpt":"A brief glimpse into the future of Orange and how we can effectively process large datasets with dask.","url":"orange-you-going-to-ask-about-dask","_type":"blog"},{"draft":false,"title":"Videos on hierarchical clustering","tags":["education"],"author":"Blaž Zupan","longExcerpt":"Six new videos explaining hierarchical clustering in Orange are now online on YouTube.","shortExcerpt":"Six new videos explaining hierarchical clustering in Orange are now online on YouTube.","url":"videos-on-hierarchical-clustering","_type":"blog"},{"draft":false,"title":"Orange in a synchrotron","tags":["workshop","addons"],"author":"Marko Toplak","longExcerpt":"We taught a three-day workshop on Orange for spectral data in UK’s national synchrotron, Diamond Light Source.","shortExcerpt":"Workshop about spectral data analysis in a synchrotron.","url":"orange-in-a-synchrotron","_type":"blog"},{"draft":false,"title":"Quick previews in Orange widgets","tags":["widgets"],"author":"Janez Demšar","longExcerpt":"Widgets can now show a quick preview of their output data.","shortExcerpt":"An exciting new feature in widgets.","url":"quick-previews-in-orange-widgets","_type":"blog"},{"draft":false,"title":"Socio-economic data at your fingertips","tags":["data","add-on","widgets","economy"],"author":"Ajda Pretnar Žagar","longExcerpt":"New World Happiness add-on for retrieving socio-economic data from the OECD database joins the Orange family","shortExcerpt":"New World Happiness add-on joins the Orange family","url":"socio-economic-data-at-your-fingertips","_type":"blog"},{"draft":false,"title":"Timeseries add-on lost a lot of weight","tags":["timeseries","line chart","spiralogram","prediction","VAR model"],"author":"Ajda Pretnar Žagar","longExcerpt":"Timeseries' visualizations are becoming fully PyQt, making them easier to maintain. We've also fixed many bugs, which should make working with the timeseries a joy once again.","shortExcerpt":"We've updated most visualizations in the Timeseries add-on","url":"timeseries-add-on-lost-a-lot-of-weight","_type":"blog"},{"draft":false,"title":"Ideas and Notes for Teachers","tags":["education"],"author":"Blaž Zupan","longExcerpt":"We are crafting free educational material to help in data science training.","shortExcerpt":"We are crafting free educational material to help in data science training.","url":"ideas-and-notes-for-teachers","_type":"blog"},{"draft":false,"title":"How to grow trees in a marmalade factory?","tags":["Education"],"author":"Zala Gruden","longExcerpt":"We visited fourthgraders in our local elementary school and taught them about clustering and data collection.","shortExcerpt":"We let the fourth grade students build their own decision tree to classify characters into professions.","url":"how-to-grow-trees-in-a-marmalade-factory","_type":"blog"},{"draft":false,"title":"An introduction to the Kaplan-Meier Estimator","tags":["survival analysis","kaplan-meier"],"author":"Ela Praznik","longExcerpt":"The Survival Analysis add-on offers accesible tools for survival analysis, the Kaplan-Meier widget being a prime example. In this blogpost we provide an introduction to the Kaplan-Meier Estimator using a simple example and show how the tool can be used in Orange on larger datasets.","shortExcerpt":"Understanding the Kaplan-Meier widget in the Survival Analysis add-on.","url":"an-introduction-to-the-kaplan-meier-estimator","_type":"blog"},{"draft":false,"title":"Confusion matrix for regression?","tags":["regression","confusion matrix","scatter plot","prediction error"],"author":"Ajda Pretnar Žagar","longExcerpt":"Confusion matrix shows classification error, but what is a suitable alternative for observing regression errors in Orange?","shortExcerpt":"How to display regression error in Orange?","url":"confusion-matrix-for-regression","_type":"blog"},{"draft":false,"title":"Predictive Modelling with Attribute Interactions","tags":["orange","interaction","addons"],"author":"Noah Novšak","longExcerpt":"The Interactions widget has been added back to Orange 3. Illustrating how to use attribute interactions to improve predictive models.","shortExcerpt":"A quick introduction to using the new Interactions widget in Orange 3","url":"predictive-modelling-with-attribute-interactions","_type":"blog"},{"draft":false,"title":"We have launched a new project on the topic of AI in schools","tags":["Google","Tides Foundation","project","visualization"],"author":"Zala Gruden","longExcerpt":"Read more about the project in the blogpost and Check out the site to find out more about the prepaired activities.","shortExcerpt":"Find out more about our new project about AI in Schools.","url":"we-have-launched-a-new-project-on-the-topic-of-ai-in-schools","_type":"blog"},{"draft":false,"title":"Training with Orange: A Tutorial at AIME 2022 in Halifax","tags":["orange","workshop"],"author":"Blaž Zupan","longExcerpt":"A conference on Artificial Intelligence in Medicine is hosting our tutorial on training of crucial mechanics behind data science and machine learning with Orange.","shortExcerpt":"A half-a day tutorial on data science training with Orange on June 14 in Halifax, Canada.","url":"training-with-orange-a-tutorial-at-aime-2022-in-halifax","_type":"blog"},{"draft":false,"title":"Orange Webinar for Educators #1: Where to Start?","tags":["orange","workshop"],"author":"Blaž Zupan","longExcerpt":"","shortExcerpt":"We are announcing a forthcoming webinar for educators and trainers.","url":"orange-webinar-for-educators-1-where-to-start","_type":"blog"},{"draft":false,"title":"LDAvis: visualization for LDA topic modelling","tags":["text mining","topic modelling","lda","visualization"],"author":"Ajda Pretnar Žagar","longExcerpt":"Text add-on recently got extended with LDAvis widget, a visualization that enables exploring word frequencies in LDA-generated topics. See how to construct LDAvis pipeline in Orange.","shortExcerpt":"Text add-on now offers a way to explain topics with LDAvis.","url":"ldavis-visualization-for-lda-topic-modelling","_type":"blog"},{"draft":false,"title":"Editing the photographs collection with the help of machine learning","tags":["orange","image analytics","images","machine learning"],"author":"Primož Godec","longExcerpt":"The core element of Orange's image analysis is embedding images in the vector space, which just became a feaster with our infrastructure upgrades. We use this opportunity to show possible ways of analyzing images through observing similar images and classifying them.","shortExcerpt":"How to use Orange's image embedding to identify similar images, classify them in categories and make an order in your photographs collection?","url":"editing-the-photographs-collection-with-the-help-of-machine-learning","_type":"blog"},{"draft":false,"title":"Machine Learning Jargon","tags":["orange","education","machine learning"],"author":"Ajda Pretnar Žagar","longExcerpt":"Data scientists have a specific language. Learn about what certain terms mean and become more confident in your data science speak!","shortExcerpt":"What do 'target variable', 'attribute', and 'learner' mean?","url":"machine-learning-jargon","_type":"blog"},{"draft":false,"title":"Orange in Classroom, pt. 2","tags":["orange","education","teaching","university"],"author":"Ajda Pretnar","longExcerpt":"Orange is being used inside and outside the classroom, by professors and students in over 300 universities around the world.","shortExcerpt":"Orange is being used in over 300 universities around the world.","url":"orange-in-classroom-pt-2","_type":"blog"},{"draft":false,"title":"Compiling Orange 2 on modern Linux","tags":["python","development","linux"],"author":"Marko Toplak","longExcerpt":"How to compile an ancient version of Orange on Ubuntu 20.04 or how to spend a cold winter evening.","shortExcerpt":"How to compile an ancient version of Orange on Ubuntu 20.04 or how to spend a cold winter evening.","url":"compiling-orange-2-on-modern-linux","_type":"blog"},{"draft":false,"title":"Visualizations 101","tags":["visualization","data mining","box plot","scatter plot","distributions"],"author":"Ajda Pretnar","longExcerpt":"When to use certain visualization and how to read it?","shortExcerpt":"How to read different visualizations?","url":"visualizations-101","_type":"blog"},{"draft":false,"title":"Explainable AI Project Meeting","tags":["project","explainable ai","teaching"],"author":"Ajda Pretnar","longExcerpt":"Orange will be used in two courses of the new Explainable AI Master's degree.","shortExcerpt":"Orange will be used in two Explainable AI courses.","url":"explainable-ai-project-meeting","_type":"blog"},{"draft":false,"title":"Characterizing Clusters with a Box Plot","tags":["clustering","explanation","box plot"],"author":"Blaž Zupan","longExcerpt":"Box Plot widget offers a simple means for explaining clusters.","shortExcerpt":"Box Plot widget offers a simple means for explaining clusters.","url":"characterizing-clusters-with-a-box-plot","_type":"blog"},{"draft":false,"title":"Semantic Analysis of Documents","tags":["semantic analysis","text mining","corpus","keywords"],"author":"Ajda Pretnar","longExcerpt":"How to use Text add-on to extract keywords from documents, score documents on keywords, and display semantic content in a map.","shortExcerpt":"How to use Text add-on for semantic analysis of documents.","url":"semantic-analysis-of-documents","_type":"blog"},{"draft":false,"title":"New in Orange: Support for CONLL-U files","tags":["conllu","text mining","corpus","lemma"],"author":"Ajda Pretnar","longExcerpt":"Orange can now work with CONLL-U files, including its lemmas, POS tags, and named entities.","shortExcerpt":"Orange can now work with CONLL-U files!","url":"new-in-orange-support-for-conll-u-files","_type":"blog"},{"draft":false,"title":"Why You Should Use Apply Domain","tags":["domain","PCA","transformation","apply domain"],"author":"Ajda Pretnar","longExcerpt":"What does Apply Domain even do? Actually, it is an extremely useful widget for all your data transformation problems!","shortExcerpt":"Apply Domain is a mystery widget with an amazing functionality.","url":"why-you-should-use-apply-domain","_type":"blog"},{"draft":false,"title":"Box Plot Alternative: Violin Plot","tags":["visualization","violin plot","box plot"],"author":"Ajda Pretnar","longExcerpt":"Box plots with an upgrade - violin plots are your new favorite visualization!","shortExcerpt":"Violin plot can tell you more than a box plot.","url":"box-plot-alternative-violin-plot","_type":"blog"},{"draft":false,"title":"PCA vs. MDS vs. t-SNE","tags":["embeddding","PCA","dimensionality reduction","workshop"],"author":"Blaž Zupan","longExcerpt":"Oh, the joy and variety of data embedding and projection techniques!","shortExcerpt":"Oh, the joy and variety of data embedding and projection techniques!","url":"pca-vs-mds-vs-t-sne","_type":"blog"},{"draft":false,"title":"Data Mining for Archaeologists, part II","tags":["archaeology","workshop","preprocess","geolocation","maps"],"author":"Ajda Pretnar","longExcerpt":"How to preprocess and map archaeological data sets.","shortExcerpt":"Mapping excavation sites in Orange.","url":"data-mining-for-archaeologists-part-ii","_type":"blog"},{"draft":false,"title":"Data Mining for Archaeologists, part I","tags":["archaeology","workshop","image analytics","amphorae"],"author":"Ajda Pretnar","longExcerpt":"A workshop about different kinds of analyses archaeologists can do in Orange.","shortExcerpt":"The many things archaeologists can do in Orange.","url":"data-mining-for-archaeologists-part-i","_type":"blog"},{"draft":false,"title":"Hands-On Training About Overfitting","tags":["education","teaching","machine learning"],"author":"Blaž Zupan","longExcerpt":"PLOS Computation Biology has just published our paper on training about overfitting.","shortExcerpt":"We have designed a course on overfitting.","url":"hands-on-training-about-overfitting","_type":"blog"},{"draft":false,"title":"Explaining Predictive Models","tags":["model explanation","explainable AI","explain","predictive modelling"],"author":"Ajda Pretnar","longExcerpt":"New Orange Explain add-on for understanding predictions and predictive models.","shortExcerpt":"New Orange add-on for explaining predictive models.","url":"explaining-predictive-models","_type":"blog"},{"draft":false,"title":"Observing Word Distribution","tags":["text mining","word distribution","bar plot","word cloud"],"author":"Ajda Pretnar","longExcerpt":"How to inspect word distribution in a corpus with a clever combination of widgets in Orange.","shortExcerpt":"How to inspect word distribution in a corpus with in Orange.","url":"observing-word-distribution","_type":"blog"},{"draft":false,"title":"Orange in Classroom","tags":["Orange","education","teaching","university"],"author":"Ajda Pretnar","longExcerpt":"Orange is actively used in classrooms at over two hundred universities from around the world.","shortExcerpt":"Orange is used in over two hundred universities around the world.","url":"orange-in-classroom","_type":"blog"},{"draft":false,"title":"2020 - Year in Code","tags":["2020","code","overview","Github"],"author":"Ajda Pretnar","longExcerpt":"Statistical report on Orange software development and educational content for 2020.","shortExcerpt":"Statistics of Orange development in 2020.","url":"2020-year-in-code","_type":"blog"},{"draft":false,"title":"How to identify fake news with document embeddings","tags":["text mining","corpus","classification"],"author":"Primož Godec and Nikola Đukić","longExcerpt":"Presenting document embeddings widget and how to identify fake news.","shortExcerpt":"New Document embedder widget and its use for classification","url":"how-to-identify-fake-news-with-document-embeddings","_type":"blog"},{"draft":false,"title":"New Video Tutorials on Text Mining","tags":["text mining","tutorial","video","twitter","sentiment analysis","embedding"],"author":"Ajda Pretnar","longExcerpt":"New video tutorials on text mining available on our YouTube channel.","shortExcerpt":"New video tutorials on text mining available on our YouTube channel.","url":"new-video-tutorials-on-text-mining","_type":"blog"},{"draft":false,"title":"Detecting Story Arcs with Orange","tags":["text mining","sentiment analysis","corpus","story arc","heat map","line chart"],"author":"Ajda Pretnar","longExcerpt":"How to detect sentiment, plot story arcs and analyze the key segments in a corpus.","shortExcerpt":"How to detect and analyze story arcs in a corpus.","url":"detecting-story-arcs-with-orange","_type":"blog"},{"draft":false,"title":"Managing Data with Edit Domain","tags":["edit","domain","data"],"author":"Ajda Pretnar","longExcerpt":"How to handle your data with Edit Domain - rename, change type, merge, sort...","shortExcerpt":"Handle your data with Edit Domain.","url":"managing-data-with-edit-domain","_type":"blog"},{"draft":false,"title":"Data Mining COVID-19 Epidemics: Part 3","tags":["covid-19","visualization","addons","trends","time"],"author":"Andreja Kovačič","longExcerpt":"Inspecting and comparing Covid-19 time trends, absolute and relative growth.","shortExcerpt":"Inspection of Covid-19 time trends.","url":"data-mining-covid-19-epidemics-part-3","_type":"blog"},{"draft":false,"title":"Data Mining COVID-19 Epidemics: Part 2","tags":["covid-19","visualization","addons","geo","time"],"author":"Robert Cvitkovič","longExcerpt":"Visualizing COVID-19 data using area and point maps and interactive timeseries.","shortExcerpt":"Visualizing COVID-19 data using maps.","url":"data-mining-covid-19-epidemics-part-2","_type":"blog"},{"draft":false,"title":"Data Mining COVID-19 Epidemics: Part 1","tags":["covid-19","feature construction","line plot"],"author":"Janez Demšar","longExcerpt":"Basic tricks for loading and analysing COVID-19 data.","shortExcerpt":"Basic tricks for loading and analysing COVID-19 data.","url":"data-mining-covid-19-epidemics-part-1","_type":"blog"},{"draft":false,"title":"Installing with Anaconda Navigator","tags":["installation","anaconda","navigator"],"author":"Ajda Pretnar","longExcerpt":"Essential information for installing Orange via Anaconda Navigator.","shortExcerpt":"Essential information for installing Orange via Anaconda Navigator.","url":"installing-with-anaconda-navigator","_type":"blog"},{"draft":false,"title":"Orange Lecture Notes","tags":["education","workshop"],"author":"Blaž Zupan","longExcerpt":"Lecture notes for Orange workshops on machine learning and data science are now available online.","shortExcerpt":"Lecture notes for Orange workshops on machine learning and data science are now available online.","url":"orange-lecture-notes","_type":"blog"},{"draft":false,"title":"What is Machine Anthropology?","tags":["machine","anthropology","big data","pivot table"],"author":"Ajda Pretnar","longExcerpt":"At the recent Machine Anthropology workshop we used Orange to explore anthropological data.","shortExcerpt":"At the recent Machine Anthropology workshop we used Orange to explore anthropological data.","url":"what-is-machine-anthropology","_type":"blog"},{"draft":false,"title":"Orange in the Cloud","tags":["cloud","server","remote"],"author":"Andrej Čopar","longExcerpt":"Use Orange remotely by running it on a remote server as a docker container.","shortExcerpt":"Use Orange remotely by running it on a remote server as a docker container.","url":"orange-in-the-cloud","_type":"blog"},{"draft":false,"title":"Look-alike Images","tags":["neighbors","images"],"author":"Blaž Zupan","longExcerpt":"We show how to use Neighbors widget on image embedding space to find image look-alikes.","shortExcerpt":"We show how to use Neighbors widget on image embedding space to find image look-alikes.","url":"look-alike-images","_type":"blog"},{"draft":false,"title":"Explaining Models: Workshop in Belgrade","tags":["workshop","belgrade","classification","nomogram","naive bayes","decision tree"],"author":"Ajda Pretnar","longExcerpt":"We explained how different models mean different things and how to interpret them at a recent tutorial in Belgrade.","shortExcerpt":"We explained how different models mean different things and how to interpret them at a recent tutorial in Belgrade.","url":"explaining-models-workshop-in-belgrade","_type":"blog"},{"draft":false,"title":"Explaining Customer Segments for Business","tags":["workshop","telco","clustering","nomogram"],"author":"Ajda Pretnar","longExcerpt":"Explaining customer base for businesses to make informed decisions. We present the case for Telco companies.","shortExcerpt":"Explaining customer base enables businesses to make informed decisions. We present the case for Telco companies.","url":"explaining-customer-segments-for-business","_type":"blog"},{"draft":false,"title":"Of Carrots and Horses and the Fear of Heights","tags":["statistical significance","hypothesis testing","p-value","multiple hypothesis testing"],"author":"Janez Demšar","longExcerpt":"A cautionary tale of imaginary friend who made too many hypotheses to test - and how Orange is no different","shortExcerpt":"A cautionary tale of imaginary friend who made too many hypotheses to test - and how Orange is no different","url":"of-carrots-and-horses-and-the-fear-of-heights","_type":"blog"},{"draft":false,"title":"On Expected Vomiting Time","tags":["model performance","confusion matrix","education"],"author":"Janez Demšar","longExcerpt":"A report of an interesting ending to a lecture about setting probability thresholds for predictive models","shortExcerpt":"Computing meaningful performance scores of models should be creative","url":"on-expected-vomiting-time","_type":"blog"},{"draft":false,"title":"Aggregate, Group By and Pivot with... Pivot Table!","tags":["pivot table","aggregate","data","groupby"],"author":"Ajda Pretnar","longExcerpt":"Orange has a brand new Pivot Table widget with many aggregation and grouping functionalities. It can be used to transform the data on-the-fly and use the output for downstream analysis.","shortExcerpt":"Orange's brand new Pivot Table widget with many aggregation and grouping functionalities.","url":"aggregate-group-by-and-pivot-with-pivot-table","_type":"blog"},{"draft":false,"title":"Doctoral Summer School","tags":["workshop","education","data science","summer school"],"author":"Ajda Pretnar","longExcerpt":"For the second year in a row we took part in the Ljubljana Doctoral Summer School, organized by the School of Economics and Business.","shortExcerpt":"This year's Data Science course at the Doctoral Summer School.","url":"doctoral-summer-school","_type":"blog"},{"draft":false,"title":"Orange at ISMB/ECCB 2019","tags":["education","bioinformatics"],"author":"Blaž Zupan","longExcerpt":"","shortExcerpt":"One of Orange's latest features is its add-on for single-cell data analytics.","url":"orange-at-ismbeccb-2019","_type":"blog"},{"draft":false,"title":"Data Science Made Easy: How To Identify Hate Comments with AI","tags":["education","text mining","workshop"],"author":"Dr. Sven Bingert & Steffen Rörtgen","longExcerpt":"How to teach text mining and data science to the 9th grade students in 60 minutes? With Orange and the analysis of hate speech on social media, of course!","shortExcerpt":"How to teach text mining and data science to the 9th grade students in 60 minutes?","url":"data-science-made-easy-how-to-identify-hate-comments-with-ai","_type":"blog"},{"draft":false,"title":"Orange at 32nd Bled eConference","tags":["workshop","education","data science"],"author":"Ajda Pretnar","longExcerpt":"We held a short workshop covering the basics of Data Science for the participants of the 32nd Bled eConference. We focused on predictive modeling and explorations of predictions.","shortExcerpt":"We held a short workshop for the participants of the 32nd Bled eConference.","url":"orange-at-32nd-bled-econference","_type":"blog"},{"draft":false,"title":"Gene Expression Profiles with Line Plot","tags":["bioinformatics","gene expression","line plot"],"author":"Ajda Pretnar","longExcerpt":"Line Plot shows profiles of data instances – each instance is a line in the plot and its profile are values across all variables in the data. We show how to explore gene expression profiles.","shortExcerpt":"We show how to explore gene expression profiles with the new Line Plot widget.","url":"gene-expression-profiles-with-line-plot","_type":"blog"},{"draft":false,"title":"Business Case Studies with Orange","tags":["business intelligence","HR","logistic regression","nomogram","predictive models"],"author":"Ajda Pretnar","longExcerpt":"At the latest workshop in Italy we taught the participants how to identify relevant business use cases and how to predict, which employees are most likely to resign in the future.","shortExcerpt":"At the latest workshop we demonstrated how to predict, which employees are most likely to resign in the future.","url":"business-case-studies-with-orange","_type":"blog"},{"draft":false,"title":"Orange at GIS Ostrava","tags":["geo","GIS","hierarchical clustering"],"author":"Blaz Zupan","longExcerpt":"In late March 2019, we have been invited to present Orange during a GIS Ostrava conference. We have shown how to work with geospatial data in Orange.","shortExcerpt":"In late March 2019, we have been invited to present Orange during a GIS Ostrava conference.","url":"orange-at-gis-ostrava","_type":"blog"},{"draft":false,"title":"The Changing Status Bar","tags":["release","Status Bar"],"author":"Blaz Zupan","longExcerpt":"We are constantly optimizing Orange's look-and-feel. New features in the status bar will simplify the user interface. We are getting rid of the infobox on the top of the control tab, and moving it to the status bar.","shortExcerpt":"We are constantly optimizing Orange's look-and-feel. New features in the status bar will simplify the user interface.","url":"the-changing-status-bar","_type":"blog"},{"draft":false,"title":"Single-Cell Data Science for Everyone","tags":["gene ontology","genomics","RNA-seq","scOrange","single cell"],"author":"Blaz Zupan","longExcerpt":"We have been in Pavia, Italy, to carry out a five-hour workshop covered both the essentials of data analysis and single cell analytics. The topics included working with marker genes, differential expression analysis, and interpretation of clusters through gene ontology analysis.","shortExcerpt":"We have been in Pavia, Italy, to carry out an introductory workshop on single-cell data science.","url":"single-cell-data-science-for-everyone","_type":"blog"},{"draft":false,"title":"The Mystery of Test & Score","tags":["cross validation","leave one out","LOO","test and score"],"author":"Ajda Pretnar","longExcerpt":"Test & Score widget is used for evaluating model performance, but what do the methods do? 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