h2o (version 2.4.3.11)

h2o.predict: H2O Model Predictions

Description

Obtains predictions from various fitted H2O model objects.

Usage

h2o.predict(object, newdata)

Arguments

object

A fitted H2OModel or H2OModelVA object for which prediction is desired.

newdata

(Optional) A H2OParsedData or H2OParsedDataVA object in which to look for variables with which to predict. If omitted, the data used to fit the model object@data

Value

• A H2OParsedData or H2OParsedDataVA object containing the predictions.

Details

This method dispatches on the type of H2O model to select the correct prediction/scoring algorithm.

See Also

h2o.glm, h2o.kmeans, h2o.randomForest, h2o.prcomp, h2o.gbm, h2o.deeplearning

Examples

library(h2o)
localH2O = h2o.init(ip = "localhost", port = 54321, startH2O = TRUE)
# Run GLM of CAPSULE ~ AGE + RACE + PSA + DCAPS
prostate.hex = h2o.importURL.VA(localH2O, path = paste("https://raw.github.com", 
  "0xdata/h2o/master/smalldata/logreg/prostate.csv", sep = "/"), key = "prostate.hex")
prostate.glm = h2o.glm(y = "CAPSULE", x = c("AGE","RACE","PSA","DCAPS"), data = prostate.hex, 
   family = "binomial", nfolds = 10, alpha = 0.5)
# Get fitted values of prostate dataset
prostate.fit = h2o.predict(object = prostate.glm, newdata = prostate.hex)
summary(prostate.fit)