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import Perceptron from '@jsmlt/jsmlt/src/supervised/linear/perceptron.js'
public class | source

Perceptron

Extends:

Estimator → Classifier → OneVsAllClassifier → Perceptron

Perceptron learner for 2 or more classes. Uses 1-vs-all classification.

Constructor Summary

Public Constructor
public

constructor(optionsUser: Object)

Constructor.

Member Summary

Public Members
public

numErrors: *[]

public

Method Summary

Public Methods
public

Callback for calculating the accuracy of the classifier on the training set in intermediate steps of training
public

createClassifier(classIndex: *): *

public

train(X: *, y: *)

Inherited Summary

From class Estimator
public abstract

predict(X: Array<Array<number>>): Array<mixed>

Make a prediction for a data set.
public abstract

train(X: Array<Array<number>>, y: Array<mixed>)

Train the supervised learning algorithm on a dataset.
From class OneVsAllClassifier
public
public abstract

createClassifier(classIndex: number): BinaryClassifier

Create a binary classifier for one of the classes.
public

Create all binary classifiers.
public

Get the class labels corresponding with each internal class label.
public

Retrieve the individual binary one-vs-all classifiers.
public

predict(X: *): *

public

predictProba(X: Array.Array<number>): Array.Array<number>

Make a probabilistic prediction for a data set.
public

trainBatch(X: Array<Array<number>>, y: Array<mixed>)

Train all binary classifiers one-by-one
public

Train all binary classifiers iteration by iteration, i.e.

Public Constructors

public constructor(optionsUser: Object) source

Constructor. Initialize class members and store user-defined options.

Params:

NameTypeAttributeDescription
optionsUser Object
  • optional

User-defined options
optionsUser.trackAccuracy trackAccuracy
  • optional
  • default: false

Whether to track accuracy during the training process. This will let the perceptron keep track of the error rate on the test set in each training iteration

Public Members

public numErrors: *[] source

public trackAccuracy: * source

Public Methods

public calculateIntermediateAccuracy() source

Callback for calculating the accuracy of the classifier on the training set in intermediate steps of training

public createClassifier(classIndex: *): * source

Create a binary classifier for one of the classes.

Override:

OneVsAllClassifier#createClassifier

Params:

NameTypeAttributeDescription
classIndex *

Return:

*

See:

  • OneVsAll#createClassifier

public train(X: *, y: *) source

Train the supervised learning algorithm on a dataset.

Override:

Estimator#train

Params:

NameTypeAttributeDescription
X *
y *

See: