Mljar-supervised

Latest version: v1.1.14

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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`

0.7.1

Bug fixes :bug:
- 173 fix bug in shap sampling
- 174 update dtreeviz package

0.7.0

Improvements
- (148) make `AutoML` scikit-learn compatible, thank you spamz23! :clap: :clap: :clap:
- (170, 171 ) improve printouts while training `AutoML`

0.6.1

Enhancements
- 145 Add EDA for input data set 125
- 135 Add ability to pause and restore the training
- 19 Add tests for ensemble save and load

Refactor
- 149 Add Time Controller
- 80 add tests for one column input

Bug fixes
- 144 AutoMlException
- 142 Error when training NN on BNP Paribas kaggle dataset

0.6.0

- Add golden features transformer (126)
- Add feature selection (133)
- Add one-hot encoding (76)
- Fixes in Neural Networks (131, 129)
- Add max_depth in Extra Trees and Random Forest (106)
- Add support for date/time features (122)

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