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Clusterer

Direct Subclass:

KMeans

Base class for clustering algorithms.

Method Summary

Public Methods
public

Assign clusters to samples.

public abstract

Run the clustering algorithm on a dataset and obtain the cluster predictions per class.

Public Methods

public cluster(X: Array<Array<number>>): Array<number> source

Assign clusters to samples.

Params:

NameTypeAttributeDescription
X Array<Array<number>>

Features per data point

Return:

Array<number>

Cluster indices assigned to input data points. For n input data points, an n-dimensional array containing the cluster assignments will be returned

public abstract train(X: Array<Array<number>>) source

Run the clustering algorithm on a dataset and obtain the cluster predictions per class.

Params:

NameTypeAttributeDescription
X Array<Array<number>>

Features per data point