Model Tuner 0.0.24a

Model Tuner Version 0.0.24a Changelog

• Updated .gitignore to incl. doctrees

• Added pickleObjects tests and updated reqs, tests passed

• Added boostrapper test and tests passed

• Adding multi class test script

• Updated Metrics Output

  • Added optl' threshold print inside return_metrics
  • KFold metric printing:
    • Added new input per_fold_print to allow user to return per fold metrics, otherwise average
    • Added tqdm output for KFold metric printing
    • Fixed KFold avg output in report_model_metrics

• Added a regression test and updating report_model_metrics to work with regression and multi class

• Augmented predict_proba test, and train_val_test_split

• Fixed pipeline_steps arg in model definition

• Refactored metrics_df in report_model_metrics for aesthetics

• Unit Tests

  • XGB early stopping multi class test
  • Added fit method tests
  • Added early stopping test
  • Added get_best_score_params() tests
  • Added return_bootstrap_metrics() tests
  • Added tests for get_preprocessing_and_feature_selection_pipeline and get_feature_selection_pipeline
  • Tested init, passed tests
  • Tested get_preprocessing_pipeline

• Imbalance Sampler

  • Addded process_imbalance_sampler() tests, passed
  • Renamed process_imbalance_sampler() to verify_imbalance_sampler

• Made return_dict optional in return_metrics

• Added openpyxl versions for all python versions in requirements.txt

• Refactor metrics, foldwise metrics and foldwise con_mat, class_labels

• Cleaned notebooks dir

• Renamed notebooks to py_example_scripts, linted files, cleaned code

• Added model_tuner version print to scripts

• Added fix for sort of pipelinesteps now optional:

  • Added required model_tuner import to xgb_multi.py
  • Added requisite model_tuner import to multi_class_test.py

• Added catboost_multi_class.py script

• Removed pip dependency from requirements