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A Study on Influence of Normalization Methods on Music Genre Classification Results Employing kNN Algorithms

This paper presents a comparison of different normalization methods applied to the set of feature vectors of music pieces. Test results show the influence of min-nlax and Zero-Mean normalization methods, employing different distance functions (Euclidean, Manhattan, Chebyshev, Minkowski) as a pre-processing for genre classification, on k-Nearest Neighbor (kNN) algorithm classification results.

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DOI
Digital Object Identifier link open in new tab 10.21936/si2013_v34.n2a.45
Category
Publikacja w czasopiśmie
Type
artykuły w czasopismach recenzowanych i innych wydawnictwach ciągłych
Language
angielski
Publication year
2013

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