CLUSTERING THROUGH OPTIMAL BAYESIAN CLASSIFICATION 1.0

Date Added: April 09, 2013 | Visits: 400

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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.

Requirements: No special requirements

Platforms: Matlab

Keyword: Assignment, Classification, Cluster, Error, Expressed, Functional, Logbayesian, Optimization

Users rating: 0/10

License: Shareware

Size: 153.6 KB

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