0.7.11

Bug fixes

• #258 Fix cant load automl when adjusted validation is used

0.7.10

Enhancements

• #250 New strategies for categorical encoding
• #257 Control algorithm order in not-so-random step

Bug fixes

• #255 Fix overwrite in adjusted models

0.7.9

Enhancements

• #249 Adjust validation type in Compete mode

0.7.8

Enhancements

• #249 Adjust validation type based on data
• #251 add more eval_metrics in regression
• #252 add traceback to error reports

Bug fixes

• #253 Fix error when text data has missing values in test fold

0.7.7

Enhancements

• #73 Optimize AUC

Bug fixes

• #136 RMSE in Extra Trees and Random Forest
• #243 Switch off Xgboost and CatBoost for multiclass with many classes (in extreme switch of Extra Trees and Random Forest)
• #245 Fix ordering of prediction columns

0.7.6

Enhancements

• #240 Change algorithm execution order for default algorithms

Bug fixes:

• #236 Wrong labels for target predictions in the case of -1, 1 target
• #238 Object of type float32 is not JSON serializable
• #239 Value Error: Input contains NaN in numpy training array

0.7.5

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 ✨

• #176 extended EDA - thanks to @shahules786

Bug fixes 🐛

• #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 🐛

• #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