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)
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 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)
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.