gaussian-mixture-model

    1.0.0 • Public • Published

    Build Status

    Gaussian Mixture Model

    Unsupervised machine learning with multivariate Gaussian mixture model which supports both offline data and real-time data stream.

    Demo: https://lukapopijac.github.io/gaussian-mixture-model/

    Installation

    npm install gaussian-mixture-model
    

    Usage

    In Node.js, simply require:

    const GMM = require('gaussian-mixture-model');

    For browser use, include dist/gmm.js file in your project. It will create a global variable GMM.

    Simple Example

    // initialize model
    var gmm = new GMM({
        weights: [0.5, 0.5],
        means: [[-25, 40], [-60, -30]],
        covariances: [
            [[400,0],[0,400]],
            [[400,0],[0,400]]
        ]
    });
     
    // create some data points
    var data = [
        [11,42],[19,45],[15,36],[25,38],[24,33],
        [-24,3],[-31,-4],[-34,-14],[-25,-5],[-16,7]
    ];
     
    // add data points to the model
    data.forEach(p => gmm.addPoint(p));
     
    // run 5 iterations of EM algorithm
    gmm.runEM(5);
     
    // predict cluster probabilities for point [-5, 25]
    var prob = gmm.predict([-5, 25]);  // [0.000009438559331418772, 0.000002126123537376676]
     
    // predict and normalize cluster probabilities for point [-5, 25]
    var probNorm = gmm.predictNormalize([-5, 25]);  // [0.8161537535012295, 0.18384624649877046]

    License

    This software is released under the MIT license.

    Install

    npm i gaussian-mixture-model

    DownloadsWeekly Downloads

    4

    Version

    1.0.0

    License

    MIT

    Unpacked Size

    9.38 kB

    Total Files

    4

    Last publish

    Collaborators

    • lukapopijac