Extract the non-linear feature from an H2O data set using an H2O deep learning model.
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
Value
Returns an H2OFrame object with as many features as the number of units in the hidden layer of the specified index.
See also
h2o.deeplearning for making H2O Deep Learning models.
Examples
if (FALSE) { # \dontrun{
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)
} # }