h2o (version 2.8.4.4)

h2o.gains: Gains and Lift Charts

Description

Construct the gains table and lift charts for binary outcome algorithms. Lift charts and gains tables are commonly applied to marketing.

Usage

h2o.gains(actual, predicted, groups=10, percents=FALSE)

Arguments

actual

An H2OParsedData object containing the predicted outcome scores. Must be a single column with the same number of rows as reference.

predicted

An H2OParsedData object containing the actual outcomes for comparison. Must be a single binary column with all entries in {0,1}.

groups

an integer containing the number of rows in the gains table. The default value is 10.

percents

(Optional) a logical that indicates whether to return results as percentage values for the cumulative lift,

Value

• An R data.frame with columns Quantile, Response.Rate, Lift, Cumulative.Lift If percents is TRUE, then Quantile, Response.Rate, and Cumulative.Lift will be in percent form.

Examples

library(h2o)
  localH2O = h2o.init()

  # Run GBM classification on prostate.csv
  prosPath = system.file("extdata", "prostate.csv", package = "h2o")
  prostate.hex = h2o.importFile(localH2O, path = prosPath, key = "prostate.hex")
  prostate.gbm = h2o.gbm(y = 2, x = 3:9, data = prostate.hex)

  # Calculate performance measures at threshold that maximizes precision
  prostate.pred = h2o.predict(prostate.gbm)
  head(prostate.pred)
  h2o.gains(prostate.hex$CAPSULE, prostate.pred[,3], percents = TRUE)