precision: precision

Description Usage Arguments Details Value Author(s) Examples

View source: R/Main.R

Description

Calculate the precision or positive predictive value for a given set of actuals and predicted probability scores.

Usage

1
precision(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, precision is defined as the proportion of observations with the event out of the total positive predictions.

Value

The precision or the positive predictive value.

Author(s)

Selva Prabhakaran [email protected]

Examples

1
2
data('ActualsAndScores')
precision(actuals=ActualsAndScores$Actuals, predictedScores=ActualsAndScores$PredictedScores)

InformationValue documentation built on May 29, 2017, 11:57 a.m.