tune_ML_models

Tune each model on a validation set with GridSearchCV.

Return each model with its best hyperparameters that have the highest F1 score and Accuracy. results_df is a dataframe with metrics and tuned parameters; models_config is a dict with model tuned params for the metrics computation stage

Parameters

• models_params_for_tuning (dict)

  A dictionary, where keys are model names and values are a dictionary of hyperparameters and value ranges to tune.

• base_flow_dataset (custom_classes.BaseFlowDataset)

  An instance of BaseFlowDataset object. Its train and test sets are used for training and tuning.

• dataset_name (str)

  A name of the dataset. Used to save tuned hyperparameters to a csv file with an appropriate filename.

• n_folds (int) – defaults to 3

  The number of folds for k-fold cross validation.