auto_scorecard |
Functions to Automatically Generate Scorecards |

best_iv |
Calculate the Best IV Value for the Binned Data |

best_vs |
The Combination of Two Bins Produces the Best Binning Result |

binning_eqfreq |
Equal Frequency Binning |

binning_eqwid |
Equal Width Binning |

binning_kmean |
The K-means Binning The k-means binning method first gives the center number, classifies the observation points using the Euclidean distance calculation and the distance from the center point, and then recalculates the center point until the center point no longer changes, and uses the classification result as the binning of the result. |

bins_chim |
Chi-Square Binning Chi-square binning, using the ChiMerge algorithm for bottom-up merging based on the chi-square test. |

bins_tree |
Automatic Binning Based on Decision Tree Automatic Binning Based on Decision Tree(rpart). |

bins_unsupervised |
Unsupervised Automatic Binning Function By setting bin_nums, perform three unsupervised automatic binning |

filter_var |
Data Filtering |

get_IV |
Function to Calculate IV Value |

noauto_scorecard |
Manually Input Parameters to Generate Scorecards |

noauto_scorecard2 |
Manually Input Parameters to Generate Scorecards The basic score is dispersed into each feature score |

plot_board |
Data Painter Function Draw K-S diagram, Lorenz diagram, lift diagram and AUC diagram. |

psi_cal |
PSI Calculation Function |

rep_woe |
Replace Feature Data by Binning Template |