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DeepLearning

  

DNNLinearCombinedClassifier

  

construct a combined neural network and linear classifier

 

Calling Sequence

Parameters

Options

Description

Calling Sequence

DNNLinearCombinedClassifier(lfc,dfc,opts)

Parameters

lfc

-

list of linear feature columns

dfc

-

list of deep neural network 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.

• 

num_classes : nonnegative integer

  

Specifies the number of distinct classes into which the data should be classified.

• 

optimizer : function or Optimizer object, or list of two functions or Optimizer objects

  

Specifies the optimizer to use to train the model. When a list of two optimizers [opt1,opt2] is provided, the first is taken to be the linear optimizer and the second the neural network optimizer. The default uses the FTRL optimizer for linear optimization and the Adagrad optimizer for neural network optimization.

Description

• 

The DNNLinearCombinedClassifier(lfc,dfc,opts) command creates a combined linear and neural network classifier for the feature columns specified in lfc and dfc.

• 

Linear classification is performed on the features in lfc and neural network classification is performed on the features in dfc.

• 

This function is part of the DeepLearning package, so it can be used in the short form DNNLinearCombinedClassifier(..) only after executing the command with(DeepLearning). However, it can always be accessed through the long form of the command by using DeepLearning[DNNLinearCombinedClassifier](..).

See Also

DeepLearning Overview

DeepLearning[DNNClassifier]

DeepLearning[DNNLinearCombinedRegressor]

DeepLearning[LinearClassifier]