R: Log Loss

logLoss {ModelMetrics} | R Documentation

## Log Loss

### Description

Calculates the log loss or entropy loss for a binary outcome

### Usage

    logLoss(...)

    ## Default S3 method:
    logLoss(actual, predicted, distribution = "binomial", ...)

    ## S3 method for class 'glm'
    logLoss(modelObject, ...)

    ## S3 method for class 'randomForest'
    logLoss(modelObject, ...)

    ## S3 method for class 'glmerMod'
    logLoss(modelObject, ...)

    ## S3 method for class 'gbm'
    logLoss(modelObject, ...)

    ## S3 method for class 'rpart'
    logLoss(modelObject, ...)

### Arguments

`...` | additional parameters to be passed the the s3 methods
`actual` | a binary vector of the labels
`predicted` | a vector of predicted values
`distribution` | the distribution of the loss function needed `binomial, poisson`
`modelObject` | the model object. Currently supported `glm, randomForest, glmerMod, gbm`

### Examples

    data(testDF)
    glmModel <- glm(y ~ ., data = testDF, family="binomial")
    Preds <- predict(glmModel, type = 'response')

    logLoss(testDF$y, Preds)
    # using s3 method for glm
    logLoss(glmModel)

[Package ModelMetrics version 1.2.2.2 Index]