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)
object | a H2OModelMetrics object of the correct type. |
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train | Retrieve the training Log Loss |
valid | Retrieve the validation Log Loss |
xval | Retrieve the cross-validation Log Loss |
# 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) # }