Retrieve either a single or many Gains/Lift tables from H2O objects.

h2o.gainsLift(object, ...)

h2o.gains_lift(object, ...)

# S4 method for H2OModel
h2o.gainsLift(object, newdata, valid = FALSE, xval = FALSE, ...)

# S4 method for H2OModelMetrics
h2o.gainsLift(object)

Arguments

object

Either an H2OModel object or an H2OModelMetrics object.

further arguments to be passed to/from this method.

newdata

An H2OFrame object that can be scored on. Requires a valid response column.

valid

Retrieve the validation metric.

xval

Retrieve the cross-validation metric.

Value

Calling this function on H2OModel objects returns a Gains/Lift table corresponding to the predict function.

Details

The H2OModelMetrics version of this function will only take H2OBinomialMetrics objects.

See also

predict for generating prediction frames, h2o.performance for creating H2OModelMetrics.

Examples

# 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
# }