h2o (version 3.44.0.3)

h2o.gainsLift: Access H2O Gains/Lift Tables

Description

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

Usage

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)

Value

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

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.

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

if (FALSE) {
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
}

Run the code above in your browser using DataCamp Workspace