h2o.auuc_normalized | R Documentation |
Retrieves the AUUC value from an H2OBinomialUpliftMetrics. If the metric parameter is "AUTO", the type of AUUC depends on auuc_type which was set before training. If you need specific normalized AUUC, set metric parameter. If "train" and "valid" parameters are FALSE (default), then the training normalized AUUC value is returned. If more than one parameter is set to TRUE, then a named vector of normalized AUUCs are returned, where the names are "train", "valid".
h2o.auuc_normalized(object, train = FALSE, valid = FALSE, metric = NULL)
object |
An H2OBinomialUpliftMetrics |
train |
Retrieve the training AUUC |
valid |
Retrieve the validation AUUC |
metric |
Specify the AUUC metric to get specific AUUC. Possibilities are NULL, "qini", "lift", "gain". |
## Not run:
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.auuc_normalized(perf)
## End(Not run)
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