gaussian-mixture-model

Gaussian Mixture Model ====================== Unsupervised machine learning with multivariate Gaussian mixture model which supports both offline data and real-time data stream. Demo: Installation ------------ ``` npm install gaussian-mixture-model ``` Simple Example -------------- ```javascript import GMM from 'gaussian-mixture-model'; // initialize model let 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 let 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 let prob = gmm.predict(-5, 25); // 0.000009438559331418772, 0.000002126123537376676 // predict and normalize cluster probabilities for point -5, 25 let probNorm = gmm.predictNormalize(-5, 25); // 0.8161537535012295, 0.18384624649877046 ``` License ------- This software is released under the MIT license.