| Function | Definition |
| autoML | Tests multiple models to find the ones which maximize the input score. |
| bayesian_search_cv | Computes the k-fold bayesian search of an estimator using a random forest model to estimate a probable optimal set of parameters. |
| best_k | Finds the k-means k based on a score. |
| cross_validate | Computes the k-fold cross-validation of an estimator. |
| elbow | Draws the an elbow curve. |
| enet_search_cv | Computes the k-fold grid search using multiple enet model. |
| gen_params_grid | Generates the estimator grid. |
| grid_search_cv | Computes the k-fold grid search of an estimator. |
| learning_curve | Draws the Learning curve. |
| lift_chart | Draws a lift chart. |
| parameter_grid | Generates the list of the different combinations of input parameters. |
| plot_acf_pacf | Draws ACF and PACF Charts. |
| prc_curve | Draws a precision-recall curve. |
| randomized_features_search_cv | Computes the k-fold grid search of an estimator using different features combinations. |
| randomized_search_cv | Computes the k-fold randomized search of an estimator. |
| roc_curve | Draws a receiver operating characteristic (ROC) curve. |
| stepwise | Uses the Stepwise algorithm to find the most suitable number of features when fitting the estimator. |
| validation_curve | Draws the validation curve. |
