Credit Scoring Modeling Toolbox

collElimination | Collinearity Elimination Automatically |

collElimination2 | Collinearity Elimination by Giving Variables' IV |

convertCutPoints | Auxiliary Function: Convert Cut Points to Cutbound |

convertType | Convert Types of Variables |

CreditData | About 20,000 fictional credit records. |

crossValidation | Cross Validation for Score Model |

Curve_Data | Auxiliary Function: Create the Appropriate Data Structure for... |

delFewValues | Delete Variables Based on Number of Different Values |

delNArate | Compute and Delete NA Rate of Variable |

delSinvalPercent | Delete Variables Based on Single-Value Percent |

dfBinningFun | Generate WOE Configuration List Automatically |

dfIV | Compute Sum IV of All X Variables |

excludeCol | Auxiliary Function: Exclude Columns in Data Frame |

executeBinFun_df | Execute Binning on Dataset |

extfromFit | Auxiliary Function: Extract Elements From Fit Object |

fread_basedict | Read Dataset Based on Data-dictionary |

genConfigList | Generate WOE Configuration List Manually |

getEqualFreqCuts | Auxiliary Function: Improved Equal-Frequency Binning |

getIV | Compute the Given Binning IV |

getWOE | Compute the Given Binning WOE |

insertElement | Auxiliary Function: Insert Elements into Vector |

LRfit | Logistic Regression Model Training by Stepwise |

LRpredict | Logistic Regression Model Predicting |

maxSinvalPercent | Get the Max Percents of All Variable's Single-Value |

myCurves | Model Performance Visualization |

myks | Compute KS Value of Score Model |

preBinningFun | Variable Pre-Binning, then Computing WOE and IV |

psi | Compute the PSI Index of Score Model |

rawPredictFun_df | Predict p Value of Entire Raw Dataset |

smbinning2 | Auxiliary Function: Optimally Binning of Given Variable |

splitData | Splitting Dataset into Train and Test Set |

sumIV | Auxiliary Function: Compute Sum IV of Given Variable |

transformScore | Transform Prediction to Standard Score |

woeEncodeFun_df | Encode Dataset as WOE |

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