CPL Clustering with Feature Costs

Authors:
Leon Bobrowski
Affiliations:
Faculty of Computer Science, Bialystok Technical University, and Institute of Biocybernetics and Biomedical Engineering, PAS, , Warsaw, Poland
Venue:
ICDM '08 Proceedings of the 8th industrial conference on Advances in Data Mining: Medical Applications, E-Commerce, Marketing, and Theoretical Aspects
Year:
2008

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Abstract

The convex and piecewise linear (CPL) criterion functions can be specified for the purposes of data clustering or unsupervised learning. The data set is in this case composed of feature vectors without additional knowledge in the form of vectors categories. The minimisation of the CPLcriterion functions allows for discovering linear dependence among feature vectors from a given data set. Introducing feature costs to the CPLcriterion functions allows to combine linear dependence examination with feature selection process.