Multiclass: Adjusted and pythonized plotting functions in mlperformance.py #848
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…honization in models.py, helper function in utilities_plot
…ision-recall, pylint, adjust optimiser
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This is the last big PR of multiclass refactor. BinaryClassification results stay the same. Notes:
cross_val_predictif there could be multiple classifiers compared on a single figure, andpredict_probafor per-classifier plots. However, if we want to measure model performance, not compare it to others, then it would be better to usepredict_probafor all plots. What are your thoughts on this?random_statefromcross_validation_mseas then it will use the global seedrnd_allfrom the database file. So, the user has control whether he wants to do all randomly (withrnd_all = None) or with a specific seed.