https://github.com/pmdartus/gaussianmixturemodel

Simple binary classification using EM algorithm
https://github.com/pmdartus/gaussianmixturemodel

Last synced: 8 days ago
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Simple binary classification using EM algorithm

• Host: GitHub
• URL: https://github.com/pmdartus/gaussianmixturemodel
• Owner: pmdartus
• Created: 2014-11-12T02:16:17.000Z (about 10 years ago)
• Default Branch: master
• Last Pushed: 2015-01-02T04:15:58.000Z (almost 10 years ago)
• Last Synced: 2024-10-18T19:01:21.996Z (28 days ago)
• Language: Python
• Size: 324 KB
• Stars: 1
• Watchers: 2
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# GaussianMixtureModel

Simple binary classification using EM algorithm

## Usage

```

pip install requirements.txt

python main.py   

```

## Optional parameters

* **-v --verbose**: Make it speak

* **-m --initMethod**: Select a specific method to initialize the EM algorithm. Available methods: *random*, *K-Means*, *Guess*. (default: *Guess*)

* **-K --nbCluster**: Required to use the *random* and *K-Means* init method. Execute the EM algorithm with a specific number of clusters. (default: 4)

* **-d --dimensions**: Number of dimensions to consider. (default: 2) 

## Data Format

Each line of the data file represent a sample in the below format:

```

Feature-Dim1 Feature-Dim2 [...] Feature-N  Class-Label

```