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Random walk distances in data clustering and applications. (English) Zbl 1261.62059

Summary: We develop a family of data clustering algorithms that combine the strengths of existing spectral approaches to clustering with various desirable properties of fuzzy methods. In particular, we show that the developed method “Fuzzy-RW”, outperforms other frequently used algorithms in data sets with different geometries. As applications, we discuss data clustering of biological and face recognition benchmarks such as the IRIS and YALE face data sets.

MSC:

62H30 Classification and discrimination; cluster analysis (statistical aspects)
60G50 Sums of independent random variables; random walks
68T10 Pattern recognition, speech recognition
65C60 Computational problems in statistics (MSC2010)
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