# iv: Information Value In scorecard: Credit Risk Scorecard

## Description

This function calculates information value (IV) for multiple x variables.

## Usage

 1 iv(dt, y, x = NULL, positive = "bad|1", order = TRUE) 

## Arguments

 dt A data frame with both x (predictor/feature) and y (response/label) variables. y Name of y variable. x Name of x variables. Default is NULL. If x is NULL, then all variables except y are counted as x variables. positive Value of positive class, default is "bad|1". order Logical, default is TRUE. If it is TRUE, the output will descending order via iv.

## Details

IV is a very useful concept for variable selection while developing credit scorecards. The formula for information value is shown below:

The log component in information value is defined as weight of evidence (WOE), which is shown as

The relationship between information value and predictive power is as follows:

 Information Value Predictive Power ----------------- ---------------- < 0.02 useless for prediction 0.02 to 0.1 Weak predictor 0.1 to 0.3 Medium predictor > 0.3 Strong predictor

## Value

Information Value

## Examples

 1 2 3 4 5 6 7 # Load German credit data data(germancredit) # information values info_value = iv(germancredit, y = "creditability") str(info_value) 

scorecard documentation built on Sept. 11, 2018, 9:03 a.m.