gaussian-mixture-model

Description

Gaussian Mixture Model (GMM) is an iterative algorithm for fitting the data with multiple normal distributions (gaussians). Can be used for classification

Details

Source

GitHub

Dialect

pharo (40% confidence)

License

MIT

Stars

1

Forks

1

Created

Feb. 22, 2021

Updated

Sept. 29, 2025

Topics

classification gaussian-mixture-models machine-learning maximum-likelihood pharo statistical-learning statistics

Categories

README excerpt

# Gaussian Mixture Model

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[![License](https://img.shields.io/badge/license-MIT-blue.svg)](https://raw.githubusercontent.com/pharo-ai/gaussian-mixture-model/master/LICENSE)

**Gaussian Mixture Model (GMM)** is an iterative algorithm for fitting the data with multiple normal distributions (gaussians). Can be used for classification.

## How to install it?

To install `gaussian-mixture-model`, go to the Playground (Ctrl+OW) in your [Pharo](https://pharo.org/) image and execute the following Metacello script (select it and press Do-it button or Ctrl+D):

```Smalltalk
Metacello new
  baseline: 'AIGaussianMixtureModel';
  repository: 'github://pharo-ai/gaussian-mixture-model/src';
  load.
```

## How to depend on it?

If you want to add a dependency on `gaussian-mixture-model` to your project, include the following lines into your baseline method:

```Smalltalk
spec
  baseline: 'AIGaussianMixtureModel'
  with: [ spec repository: 'github://pharo-ai/gaussian-mixture-model/src' ].
```

If you are new to baselines and Metacello, check out the [Baselines](https://github.com/pharo-open-documentation/pharo-wiki/blob/master/General/Baselines.md) tutorial on Pharo Wiki.

## How to use it?