npv: npv

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

Description

Calculate the negative predictive value for a given set of actuals and predicted probability scores.

Usage

npv(actuals, predictedScores, threshold = 0.5)

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.
threshold	If predicted value is above the threshold, it will be considered as an event (1), else it will be a non-event (0). Defaults to 0.5.

Details

For a given given binary response actuals and predicted probability scores, negative predictive value is defined as the proportion of observations without the event out of the total negative predictions.

Value

The negative predictive value for a given set of actuals and probability scores, with the specified cutoff threshold.

Author(s)

Selva Prabhakaran [e-mail]

Examples

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

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