| cleanse | Cleansing the dataset for classification modeling |
| cleanse.data.frame | Cleansing the dataset for classification modeling |
| cleanse.split_df | Cleansing the dataset for classification modeling |
| compare_diag | Diagnosis of train set and test set of split_df object |
| compare_performance | Compare model performance |
| compare_plot | Comparison plot of train set and test set |
| compare_target_category | Comparison of categorical variables of train set and test set |
| compare_target_numeric | Comparison of numerical variables of train set and test set |
| extract_set | Extract train/test dataset |
| matthews | Compute Matthews Correlation Coefficient |
| performance_metric | Calculate metrics for model evaluation |
| plot_cutoff | Visualization for cut-off selection |
| plot_performance | Visualization for ROC curve |
| run_models | Fit binary classification model |
| run_performance | Apply calculate performance metrics for model evaluation |
| run_predict | Predict binary classification model |
| sampling_target | Extract the data to fit the model |
| split_by | Split Data into Train and Test Set |
| split_by.data.frame | Split Data into Train and Test Set |
| summary.split_df | Summarizing split_df information |
| treatment_corr | Diagnosis and removal of highly correlated variables |