kmeans-ts
    TypeScript icon, indicating that this package has built-in type declarations

    1.0.4 • Public • Published

    K-Means-TS

    💹 K-means and k-means++ clustering implementation. A Typescript rewrite of Skmeans-JS

    Quick Start

    Installation

    npm i kmeans-ts
    

    Importation

    import kmeans from "kmeans-ts";

    If you want to access the interfaces or utilities within the package, use

    import { KMeans, Vectors, Utils } from "kmeans-ts";

    Implementation

    var input_data: Array<Array<number>> = [
    	[1, 12, 14, 4, 25, 35, 22, 3, 14, 5, 51, 2, 23, 24, 15],
    	[7, 34, 15, 34, 17, 11, 34, 2, 35, 18, 52, 34, 33, 21],
    	[5, 19, 35, 17, 35, 18, 12, 45, 23, 56, 23, 45, 16, 3]
    ];
    var output: Array<Array<number>> = kmeans(input_data, 3, "kmeans");

    Returns

    {
    	"iterations": 1,
    	"k": 3,
    	"indexes": [2,1,0],
    	"centroids": [
    		[5,19,35,17,35,18,12,45,23,56,23,45,16,3,0],
    		[7,34,15,34,17,11,34,2,35,18,52,34,33,21,0],
    		[1,12,14,4,25,35,22,3,14,5,51,2,23,24,15]
    	]
    }

    Functionality & Params

    Param Description Sample Type Required
    Input Data Array of values to be clustered. Can be multi-dimensional Array<number>, Array<Array<number>> Yes
    K Num clusters number Yes
    Centroids Initializes centroids. Kmeans for random, Kmeans++ for the K-means++ algorithm. Will attempt to find them if not provided. String Optional
    Iterations Max num of iterations. Default is 10000 number Optional

    Returns the following object:

    Return value Description Sample type
    Iterations Num iterations undergone number
    K Num clusters number
    Centroids Centroid values for each cluster Array<number>
    Indexes Index of centroid for each value of input array Array<Array<number>>

    Further Examples

    // K-means w/ 4 clusters & random centroid initialization
    var kmeans: KMeans = kmeans(input_data, 4, "kmeans");
    
    // K-means w/ 3 clusters & initial centroids included
    var kmeans: KMeans = kmeans(input_data, 3, [
    	[3, 1, 5],
    	[7, 2, 6],
    	[3, 8, 6]
    ]);
    
    // K-means++ w/ 5 clusters
    var kmeans: KMeans = kmeans(input_data, 5, "kmeans++");
    
    // K-means w/ 7 clusters, random centroids, and 15 max iterations
    var kmeans: KMeans = kmeans(input_data, 7, null, 15);

    K-Means-TS can be seen in MTG-Meta-TS

    Development Setup

    Simply clone the repository, then if you would like to generate a new ts-config run

    --ts-config init
    

    This will create a tsconfig.json file. If you are using VSCode, enter Ctrl-Shift-B and then tsc:watch, which will auto-compile TS to JS. You can also use tsc <filename> to compile from ts to js.

    This project uses tsdx for compilation and minification. You can run that with npm start

    To test this project, you can navigate to /example and run the testing ground with either ts-node testing_ground.ts, or by compiling it to JS and then running it in the terminal with node testing_ground.js

    Alternatively, you can install the awesome VSCode extension Code Runner, which is very convenient

    Contributing

    1. Fork K-Means-TS here
    2. Create a feature branch (git checkout -b feature/fooBar)
    3. Commit your changes (git commit -am 'Add some fooBar')
    4. Push to the branch (git push origin feature/fooBar)
    5. Create a new Pull Request

    Meta

    Adapted from @Solzimer's Skmeans-JS by @GoldinGuy

    Distributed under the MIT license. See LICENSE for more information.

    Install

    npm i kmeans-ts

    DownloadsWeekly Downloads

    18

    Version

    1.0.4

    License

    MIT

    Unpacked Size

    71 kB

    Total Files

    12

    Last publish

    Collaborators

    • goldinguy