Releases 1.2.0
Changing cross-validation (CV) in VERIFY to LOOCV for datasets with less than 50 points
Changing MAPIE in PREDICT to LOOCV for datasets with less than 50 points
By default, RFECV uses LOOCV for small datasets and 5-fold CV for larger datasets
The external test set is chosen more evenly along the range of y values (not fully random)
Changing the format of the VERIFY plot, from donut to bar plots
Automatic KN data splitting for databases with less than 250 datapoints
Change CV_test from ShuffleSplit to Kfold
Predictions from CV are now represented in a graph and stored in a CSV
Changing the ROBERT score to depend more heavily on results from CV
Fixing auto_test (now it works as specified in the documentation)
Adding clas predictions to report PDF
Adding new pytests that cover the ROBERT score section from the report PDF
Adding the EVALUATE module to evaluate linear models with user-defined descriptors and partitions
Adding Pearson heatmap in PREDICT for the two models, with individual variable correlation analysis
Adding y-distribution graphs and analysis of uniformity
Major changes to the report PDF file to include sections rather than modules
Improving explanation of the ROBERT score on Read The Docs
Printing coefficients in MVL models inside PREDICT.dat
Fixing bug in RFECV for classification problems, now it uses RandomForestClassifier()
Automatic recognition of classification problems
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