## jacobemerick/kmeans

k-means clustering implemented in PHP

Installs: 2 516

Dependents: 0

Suggesters: 0

Security: 0

Stars: 8

Watchers: 0

Forks: 3

Open Issues: 3

Requires

- php: >=5.3

This package is **not** auto-updated.

Last update: 2020-07-06 10:59:09 UTC

# README

This handly little class will calculate the k-means for a set of observations using PHP. k-means is a cool way to cluster data into groups based on relation - like clustering geographical data (using lat/lng) into a digestible summary. It is useful for detecting patterns in large data sets.

## Usage

Let's say that you wanted to cluster a data set. The data must be in a multi-dimensional array, each value a numeric, though the size of each row has no constraint (n-dimensions ftw).

$array = [ [1, 1, 3], [3, 7, 6], [5, 8, 3], [1, 2, 1], [9, 10, 8], [4, 4, 4], ];

By observation you may suspect that this data can be clustered into 3 separate sets. To test, run the class.

$kmeans = new Jacobemerick\KMeans\Kmeans($array); $kmeans->cluster(3); // cluster into three sets $clustered_data = $kmeans->getClusteredData(); // $clustered_data = [ // [[1, 1, 3], [1, 2, 1]], // [[3, 5, 6], [5, 4, 3], [4, 4, 4]], // [[9, 10, 8]], // ]; $centroids = $kmeans->getCentroids(); // $centroids = [ // [1, 1.5, 2], // [4, 4.33, 4.33], // [9, 10, 8], // ];

Note: larger data sets will be more consistent - if you run this example multiple times your results may vary.

## Installation

Through composer:

`$ composer require jacobemerick/kmeans:~1.0`