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2.1.0
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In classification problems now we can use 2 different categorial class labels (e.g., "active"/"inactive").
Changing the way of selecting the 10 first initial points in Bayesian Optimization (now using Latin Hypercube Sampling)
Deleting first the most correlated features in CURATE module
Sorting the columns and rows in the csv files to ensure reproducibility
Using only KNN imputer if you have more than 100 datapoints
Fixing RFECV (each model now has its own set of descriptors after feature selection)
Fixing bug in the AQME module when using --csv_test
Changing pkg_resources to importlib.resources to avoid deprecation warnings
Fixed bug when selecting test set datapoints with the EVEN option
Fixed bug in the name of extra_q1 and extra_q5 splitting methods
Updating packages versions in setup.py
Molssi databases link in easyROB GUI
Default split is 'RND' for classification problems
The sklearn-intelex accelerator was removed
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