ModelMetrics (version 1.2.2)

logLoss: Log Loss

Description

Calculates the log loss or entropy loss for a binary outcome

Usage

logLoss(...)
# S3 method for default
logLoss(actual, predicted, distribution = "binomial", ...)
# S3 method for glm
logLoss(modelObject, ...)
# S3 method for randomForest
logLoss(modelObject, ...)
# S3 method for glmerMod
logLoss(modelObject, ...)
# S3 method for gbm
logLoss(modelObject, ...)
# S3 method for 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

# NOT RUN {
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)

# }

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