ks_stat: ks_stat

In InformationValue: Performance Analysis and Companion Functions for Binary Classification Models

Description

Compute the Kolmogorov-Smirnov statistic

Usage

ks_stat(actuals, predictedScores, returnKSTable = FALSE)

Arguments

actuals	The actual binary flags for the response variable. It can take a numeric vector containing values of either 1 or 0, where 1 represents the 'Good' or 'Events' while 0 represents 'Bad' or 'Non-Events'.
predictedScores	The prediction probability scores for each observation. If your classification model gives the 1/0 predcitions, convert it to a numeric vector of 1's and 0's.
returnKSTable	If set to TRUE, returns the KS table used to calculate the KS statistic instead. Defaults to FALSE.

Details

Compute the KS statistic for a given actuals and predicted scores for a binary response variable. KS statistic is calculated as the maximum difference between the cumulative true positive and cumulative false positive rate. Set returnKSTable to TRUE to see the calculations from ks_table.

Value

The KS statistic for a given actual values of a binary response variable and the respective prediction probability scores.

Author(s)

Selva Prabhakaran [e-mail]

Examples

data('ActualsAndScores')
ks_stat(actuals=ActualsAndScores$Actuals, predictedScores=ActualsAndScores$PredictedScores)

InformationValue documentation built on May 1, 2019, 9:12 p.m.