cluster.KMeans

Usage

import { KMeans } from 'machinelearn/cluster';

const kmean = new KMeans({ k: 2 });
const clusters = kmean.fit([[1, 2], [1, 4], [1, 0], [4, 2], [4, 4], [4, 0]]);

const result = kmean.predict([[0, 0], [4, 4]]);
// results in: [0, 1]

Constructors

constructor

Methods

fit
fromJSON
predict
toJSON

Constructors

constructor

⊕ KMeans(__namedParameters: `object`)

Defined in cluster/k_means.ts:34

Parameters:

Param	Type	Default
options.distance		'euclidean'
options.k	number	3
options.maxIteration	number	300
options.randomState	number	0

Returns: KMeans

Methods

λ fit

Compute k-means clustering.

Defined in cluster/k_means.ts:75

Parameters:

Param	Type	Default	Description
X	number[][]	null	array-like or sparse matrix of shape = [n_samples, n_features]

Returns:

void

λ fromJSON

Restores the model from checkpoints

Defined in cluster/k_means.ts:163

Parameters:

Param	Type	Default
centroids	number[][]	null
clusters	number[]	null
options.k	number	null

Returns:

void

λ predict

Predicts the cluster index with the given X

Defined in cluster/k_means.ts:134

Parameters:

Param	Type	Default	Description
X	number[][]	null	array-like or sparse matrix of shape = [n_samples, n_features]

Returns:

number[]

λ toJSON

Get the model details in JSON format

Defined in cluster/k_means.ts:145

Returns:

Param	Type	Description
k	number	undefined