Credit Scorecard Modelling Utils

categorical_iv | IV table for individual categorical variable |

cat_new_class | Clubbing class of categorical variables with low population... |

club_cat_class | Clubbing class of a categorical variable with low population... |

cv_filter | Variable reduction based on Cramer's V filter |

cv_table | Pairwise Cramer's V among a list of categorical variables |

cv_test | Cramer's V value between two categorical variables |

dtree_split_val | Getting the split value for terminal nodes from decision tree |

dtree_trend_iv | Recursive Decision Tree partitioning with monotonic event... |

fn_conf_mat | Creates confusion matrix and its related measures |

fn_cross_index | Creates random index for k-fold cross validation |

fn_error | Computes error measures between observed and predicted values |

fn_mode | Calculating mode value of a vector |

fn_target | Redefines target value |

gini_table | Performance measure table with Gini coefficient,... |

gradient_boosting_parameters | Hyperparameter optimisation or parameter tuning for Gradient... |

iv_filter | Variable reduction based on Information Value filter |

iv_table | WOE and IV table for list of numerical and categorical... |

missing_val | Missing value imputation |

num_to_cat | Binning numerical variables based on cuts from IV table |

others_class | Clubbing of classes of categorical variable with low... |

random_forest_parameters | Hyperparameter optimisation or parameter tuning for Random... |

sampling | Random sampling of data into train and test |

scalling | Converting coefficients of logistic regression into scores... |

scoring | Scoring a dataset with class based on a scalling logic to... |

support_vector_parameters | Hyperparameter optimisation or parameter tuning for Suppert... |

univariate | Univariate analysis of variables |

vif_filter | Removing multicollinearity from a model using vif test |

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