# 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, distribution = "bernoulli",
training_frame = prostate, validation_frame = prostate, nfolds=3)
h2o.gainsLift(model) ## extract training metrics
h2o.gainsLift(model, valid=TRUE) ## extract validation metrics (here: the same)
h2o.gainsLift(model, xval =TRUE) ## extract cross-validation metrics
h2o.gainsLift(model, newdata=prostate) ## score on new data (here: the same)
# Generating a ModelMetrics object
perf <- h2o.performance(model, prostate)
h2o.gainsLift(perf) ## extract from existing metrics object
# }
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