DeepLearning/DNNLinearCombinedRegressor - Help

Online Help

All Products    Maple    MapleSim


Home : Support : Online Help : DeepLearning/DNNLinearCombinedRegressor

DeepLearning

  

DNNLinearCombinedRegressor

  

construct a combined neural network and linear regressor

 

Calling Sequence

Parameters

Options

Description

Calling Sequence

DNNLinearCombinedRegressor(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.

• 

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

• 

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

• 

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

See Also

DeepLearning Overview

DeepLearning[DNNLinearCombinedClassifier]

DeepLearning[DNNRegressor]

DeepLearning[LinearRegressor]