- Removed force_finite parameter in r2 score - regression - add roc_auc metric in kfold - classification
0.13.10
- Fixed bug causing upgrade to fail
0.13.0
- Added new parameter 'select_models' that enables you to select only a few models to train with instead of using all models at once. - Added progress bar when training models - Added more understandable error message with fixes indicated - Fixed key error bug in use_model when specifying metric - Removed r2 score metric from classification
0.12.3
- Fixed bug that stopped models from training due to inconsistent number of columns - Temporarily disabled using over, under or over_under sampling techniques when using kf=True - Added a new parameter y to 'visualize' and 'show' methods to indicate the target.
0.12.0
- If model is unable to properly compute metrics, it's value is replaced with np.nan - Added 'encode' parameter in split method to encode categorical columns - Added 'missing' values parameter in split method for filling missing values for both numerical and categorical columns.