Access H2O Gains/Lift Tables
Retrieve either a single or many Gains/Lift tables from H2O objects.
h2o.gainsLift(object, ...) h2o.gains_lift(object, ...) ## S4 method for signature 'H2OModel' h2o.gainsLift(object, newdata, valid = FALSE, xval = FALSE, ...) ## S4 method for signature 'H2OModelMetrics' h2o.gainsLift(object)
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.Calling this function on H2OModel objects returns a Gains/Lift table corresponding to the predict
function.
The H2OModelMetrics version of this function will only take H2OBinomialMetrics objects.
## 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 ## End(Not run)
predict
for generating prediction frames, h2o.performance
for creating H2OModelMetrics .