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Expmax is an expectation maximization (EM) library. It makes use of a gaussian mixture model.
This library allows data clustering of n-dimensional datasets given the amount of clusters wanted.
.
├── core
│ ├── expmax_core.ts
│ └── gaussian_mixture_core.ts
├── engines
│ └── expmax.ts
├── errors.ts
├── index.ts
├── types.ts
└── utils
└── math.tsPlease refer to the NPM custom commands section
First install the library
npm install expmaxExample:
import {ExpMax} from 'expmax';
// Dataset should have data points with same vector space dimension
const dataset: IDataset = {
'points': [
[1.1,1],
[1,2],
[2,2],
[2,1],
[15,15],
[15,16],
],
'label':'test',
};
const opts: IEmOptions = {
'clusterQt':2, // Quantity of clusters you want to fit
'maxEpochs':1000, // Maximum training cycles
'threshold': 2e-16 // Threshold (epsilon) used to define convergence
}
const model = new ExpMax(dataset, opts); // Instanciate the model with random values
const trainedModel = model.train() // Train it
console.log(trainedModel);
/*
Output:
[
{
mu: [ 15.55, 16 ],
sigma: [ [Array], [Array] ],
vectorSpaceDim: 2,
pi: 0.3333333333333333,
gamma: [
1.8570742387734104e-153,
3.512200996873401e-50,
3.128974029587457e-48,
7.275927146729349e-54,
1,
1
]
},
{
mu: [ 1.525, 1.5 ],
sigma: [ [Array], [Array] ],
vectorSpaceDim: 2,
pi: 0.6666666666666666,
gamma: [ 1, 1, 1, 1, 5.362024468745314e-82, 1.955669841306763e-88 ]
}
]*/.train(): Trains the model then return clusters.update(newDataset): Updates dataset then trains the model and returns new clusters
build: Build the JavaScript files.build:watch: Build the JavaScript files in watch mode.test: Run jest in test mode.test:watch: Run jest in interactive test mode.docs: Generate the docs directory.lint: Runs linter on the whole project.
- https://towardsdatascience.com/gaussian-mixture-models-explained-6986aaf5a95
- https://perso.telecom-paristech.fr/bonald/documents/gmm.pdf
@lovasoa: https://github.com/lovasoa/expectation-maximization
This lib helped me a great deal, thanks.
Bastien GUIHARD