DeepLearning
DNNRegressor
construct a neural network regressor
Calling Sequence
Parameters
Options
Description
Compatibility
DNNRegressor(fc,opts)
fc
-
list of feature columns
opts
(optional) one or more keyword options described below
hidden_units : list of nonnegative integers
Specifies the number of hidden nodes in the neural network at each level.
optimizer : function or Optimizer object
Specifies the optimizer to use to train the model. The default is the Adagrad optimizer.
The DNNRegressor(fc,opts) command creates a deep neural network regressor for the feature columns specified in fc.
This function is part of the DeepLearning package, so it can be used in the short form DNNRegressor(..) only after executing the command with(DeepLearning). However, it can always be accessed through the long form of the command by using DeepLearning[DNNRegressor](..).
The DeepLearning[DNNRegressor] command was introduced in Maple 2018.
For more information on Maple 2018 changes, see Updates in Maple 2018.
See Also
DeepLearning Overview
DeepLearning[DNNClassifier]
DeepLearning[DNNLinearCombinedRegressor]
DeepLearning[LinearRegressor]
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