
handle: 11104/0004771
Matrix factorization or factor analysis is an important task helpful in the analysis of high dimensional real world data. There are several well known methods and algorithms for factorization of real data but many application areas including information retrieval, pattern recognition and data mining require processing of binary rather than real data. Unfortunately, the methods used for real matrix factorization fail in the latter case. In this paper we introduce background and initial version of Genetic Algorithm for binary matrix factorization.
machine learning, Boolean factorization, feature extraction, data mining, binary data, genetic algorithms
machine learning, Boolean factorization, feature extraction, data mining, binary data, genetic algorithms
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