DNNRegressor - Maple Help

DeepLearning

 DNNRegressor
 construct a neural network regressor

 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.