h2o (version 3.10.3.6)

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 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)
h2o.init()
prosPath = system.file("extdata", "prostate.csv", package = "h2o")
prostate.hex = h2o.importFile(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)

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