logLoss {ModelMetrics} | R Documentation |
Calculates the log loss or entropy loss for a binary outcome
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, ...)
... |
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 |
modelObject |
the model object. Currently supported |
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)