Retrieves the log loss output for a H2OBinomialMetrics or H2OMultinomialMetrics object If "train", "valid", and "xval" parameters are FALSE (default), then the training Log Loss value is returned. If more than one parameter is set to TRUE, then a named vector of Log Losses are returned, where the names are "train", "valid" or "xval".

h2o.logloss(object, train = FALSE, valid = FALSE, xval = FALSE)

Arguments

object

a H2OModelMetrics object of the correct type.

train

Retrieve the training Log Loss

valid

Retrieve the validation Log Loss

xval

Retrieve the cross-validation Log Loss

Examples

# NOT RUN {
library(h2o)
h2o.init()

f <- "https://s3.amazonaws.com/h2o-public-test-data/smalldata/junit/cars_20mpg.csv"
cars <- h2o.importFile(f)
cars["economy_20mpg"] <- as.factor(cars["economy_20mpg"])
predictors <- c("displacement", "power", "weight", "acceleration", "year")
response <- "economy_20mpg"
cars_splits <- h2o.splitFrame(data =  cars, ratios = .8, seed = 1234)
train <- cars_splits[[1]]
valid <- cars_splits[[2]]
car_drf <- h2o.randomForest(x = predictors,
                            y = response,
                            training_frame = train,
                            validation_frame = valid)
h2o.logloss(car_drf, train = TRUE, valid = TRUE)
# }