h2o (version 3.2.0.3)

h2o.deepfeatures: Feature Generation via H2O Deep Learning Model

Description

Extract the non-linear feature from an H2O data set using an H2O deep learning model.

Usage

h2o.deepfeatures(object, data, layer = 1)

Arguments

object

An H2OModel object that represents the deep learning model to be used for feature extraction.

data

An H2OFrame object.

layer

Index of the hidden layer to extract.

Value

• Returns an H2OFrame object with as many features as the number of units in the hidden layer of the specified index.

See Also

link{h2o.deeplearning} for making deep learning models.

Examples

library(h2o)
localH2O = h2o.init()
prosPath = system.file("extdata", "prostate.csv", package = "h2o")
prostate.hex = h2o.importFile(localH2O, path = prosPath)
prostate.dl = h2o.deeplearning(x = 3:9, y = 2, training_frame = prostate.hex,
                               hidden = c(100, 200), epochs = 5)
prostate.deepfeatures_layer1 = h2o.deepfeatures(prostate.dl, prostate.hex, layer = 1)
prostate.deepfeatures_layer2 = h2o.deepfeatures(prostate.dl, prostate.hex, layer = 2)
head(prostate.deepfeatures_layer1)
head(prostate.deepfeatures_layer2)