Bug fixes - (216) Raise exception when all models with error - (234) Fix target with first empty value
0.7.4
Enhancements - 184 Change Keras+TF Neural Networks to scikit-learn MLP - 233 Limit staking number of classes and models - 232 Remove Linear model from Compete mode - 208 Improve importance computation for large number of columns - 205 Remove small learning rates for Xgboost
Bug fixes: - 231 Restricted characters in feature_neams in Xgboost - 227 Fix strings in golden_features.json - thank you SuryaThiru! - 215 Assure at least 20 samples (or k_folds) for each class
Docs update: - 213 Update docs in AutoML - thank you shahules786!
0.7.3
New features :sparkles: - 176 extended EDA - thanks to shahules786
Bug fixes :bug: - 201 error in golden features sampling - 199 bug for float multi-class labels - 196 add exception for empty data - 195 set threshold for accuracy metric instead f1 - 194 ensemble should be best model if has more than 1 model - 193 fixed predict aflter model loading - 192 update pyarrow - 191 hide shap warnings - 190 fix in preprocessing - 188 fix type in feature selection - thanks to uditswaroopa
0.7.2
Bug fixes :bug: - 187 fix wrong order in golden features step - 186 fix `_get_results_path` - 185 fix models loading - 184 exception when drop all features during selection - 182 catch exceptions from model and log to `errors.md` - 181 remove forbidden characters in EDA - 177 change docstring to google-stype - 175 remove `tuning_mode` parameter from `AutoML`