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DeepLearning

  

DNNRegressor

  

construct a neural network regressor

 

Calling Sequence

Parameters

Options

Description

Compatibility

Calling Sequence

DNNRegressor(fc,opts)

Parameters

fc

-

list of feature columns

opts

-

(optional) one or more keyword options described below

Options

• 

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.

Description

• 

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](..).

Compatibility

• 

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]