Extract the non-linear feature from an H2O data set using an H2O deep learning model.
h2o.deepfeatures(object, data, layer)
object | An H2OModel object that represents the deep learning model to be used for feature extraction. |
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data | An H2OFrame object. |
layer | Index (integer) of the hidden layer to extract |
Returns an H2OFrame object with as many features as the number of units in the hidden layer of the specified index.
h2o.deeplearning
for making H2O Deep Learning models.
# 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) # }