pmdartus / GaussianMixtureModel

Simple binary classification using EM algorithm

GaussianMixtureModel

Simple binary classification using EM algorithm

Usage

pip install requirements.txt
python main.py <training file> <unlabeled file> <output file>

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