Fully Automatic Generation of Scorecards

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Documentation for package ‘autoScorecard’ version 0.3.0

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

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
comparison_two	Compare the Distribution of the Two Variable Draw box plots, cdf plot , QQ plots and histograms for two data.
comparison_two_data	Compare the Distribution of the Two Data
data_detect	Data Description Function
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