R/models.R
h2o.aecu.RdRetrieves the AECU value from an H2OBinomialUpliftMetrics. You need to specificy the type of AECU using metric parameter. Defaults "qini". Qini AECU equals the Qini value. If "train" and "valid" parameters are FALSE (default), then the training AECU value is returned. If more than one parameter is set to TRUE, then a named vector of AECUs are returned, where the names are "train", "valid".
h2o.aecu(object, train = FALSE, valid = FALSE, metric = "qini")if (FALSE) { # \dontrun{
library(h2o)
h2o.init()
f <- "https://s3.amazonaws.com/h2o-public-test-data/smalldata/uplift/criteo_uplift_13k.csv"
train <- h2o.importFile(f)
train$treatment <- as.factor(train$treatment)
train$conversion <- as.factor(train$conversion)
model <- h2o.upliftRandomForest(training_frame=train, x=sprintf("f%s",seq(0:10)), y="conversion",
ntrees=10, max_depth=5, treatment_column="treatment",
auuc_type="AUTO")
perf <- h2o.performance(model, train=TRUE)
h2o.aecu(perf)
} # }