Retrieves the mean per class error from an H2OBinomialMetrics. If "train", "valid", and "xval" parameters are FALSE (default), then the training mean per class error value is returned. If more than one parameter is set to TRUE, then a named vector of mean per class errors are returned, where the names are "train", "valid" or "xval".
h2o.mean_per_class_error(object, train = FALSE, valid = FALSE, xval = FALSE)
object | An H2OBinomialMetrics object. |
---|---|
train | Retrieve the training mean per class error |
valid | Retrieve the validation mean per class error |
xval | Retrieve the cross-validation mean per class error |
h2o.mse
for MSE, and h2o.metric
for the
various threshold metrics. See h2o.performance
for
creating H2OModelMetrics objects.
# NOT RUN { library(h2o) h2o.init() prostate_path <- system.file("extdata", "prostate.csv", package = "h2o") prostate <- h2o.uploadFile(prostate_path) prostate[, 2] <- as.factor(prostate[, 2]) model <- h2o.gbm(x = 3:9, y = 2, training_frame = prostate, distribution = "bernoulli") perf <- h2o.performance(model, prostate) h2o.mean_per_class_error(perf) h2o.mean_per_class_error(model, train=TRUE) # }