CLUSTERING THROUGH OPTIMAL BAYESIAN CLASSIFICATION
The package contains function for performing soft clustering.
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A new soft clustering algorithm is presented (Clustering through Optimal Bayesian Classification). The algorithm does not depend on random initializations, and it contains a native metric to select the optimal number of clusters.
The clustering algorithm minimizes the log-Bayesian risk (classification error) which can be expressed from the soft cluster assignment. The log-Bayesian risk is given as an optimization functional to perform the clustering. An Expectation-Maximization-like algorithm is proposed in order to minimize the proposed functional.
CPU and GPU implementations are included.
Cite As
Lionel (2026). CLUSTERING THROUGH OPTIMAL BAYESIAN CLASSIFICATION (https://www.mathworks.com/matlabcentral/fileexchange/33276-clustering-through-optimal-bayesian-classification), MATLAB Central File Exchange. Retrieved .
General Information
- Version 1.2.0.0 (157 KB)
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
