Estimator - Maple Help
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DeepLearning

  

Estimator

  

estimator object

 

Description

Generating Estimators

Operations with Estimators

Examples

Compatibility

Description

• 

An Estimator is an object which encapsulates a high-level interface which encapsulates tasks for training, evaluation, and prediction with machine learning models.

Generating Estimators

• 

To construct an Estimator object encapsulating a certain classification or regression task, see the DeepLearning Overview section on Estimators.

Operations with Estimators

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The following functions can be performed with an Estimator.

Evaluate

Predict

Train

 

Examples

Train a deep neural network classifier to recognize whether a point is within a circle centered at the origin with radius 1. We begin by generating some input data to train the model.

We can now define an Estimator, in this case a DNNClassifier, to process the input.

(1)

(2)

(3)

With our classifier thus trained, we can make predictions about additional points.

Compatibility

• 

The DeepLearning[Estimator] command was introduced in Maple 2018.

• 

For more information on Maple 2018 changes, see Updates in Maple 2018.

See Also

DeepLearning Overview

 


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