h2o.deepfeatures {h2o} | R Documentation |
Feature Generation via H2O Deep Learning
Description
Extract the non-linear feature from an H2O data set using an H2O deep learning model.
Usage
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 |
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
## 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)
[Package h2o version 3.44.0.3 Index]