h2o.deepfeatures function

Feature Generation via H2O Deep Learning

Feature Generation via H2O Deep Learning

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

h2o.deepfeatures(object, data, layer)

Arguments

  • object: An H2OModel object that represents the deep learning model to be used for feature extraction.
  • data: An H2OFrame object.
  • layer: Index (integer) of the hidden layer to extract

Returns

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

Examples

## Not run: library(h2o) h2o.init() prostate_path = system.file("extdata", "prostate.csv", package = "h2o") prostate = h2o.importFile(path = prostate_path) prostate_dl = h2o.deeplearning(x = 3:9, y = 2, training_frame = prostate, hidden = c(100, 200), epochs = 5) prostate_deepfeatures_layer1 = h2o.deepfeatures(prostate_dl, prostate, layer = 1) prostate_deepfeatures_layer2 = h2o.deepfeatures(prostate_dl, prostate, layer = 2) head(prostate_deepfeatures_layer1) head(prostate_deepfeatures_layer2) ## End(Not run)

See Also

h2o.deeplearning for making H2O Deep Learning models.

  • Maintainer: Tomas Fryda
  • License: Apache License (== 2.0)
  • Last published: 2024-01-11