TY - JOUR T1 - Comparative Analysis of SVM, k-NN and Logistic Regression Methods in Classifying Turkish Music Genres AU - Özbalcı, Mehmet Cüneyt AU - Bilgin, Turgay Tugay PY - 2026 DA - April Y2 - 2026 DO - 10.38088/jise.1809289 JF - Journal of Innovative Science and Engineering JO - JISE PB - Bursa Technical University WT - DergiPark SN - 2602-4217 SP - 172 EP - 188 VL - 10 IS - 1 LA - en AB - Music genre classification represents a fundamental challenge within the field of Music Information Retrieval (MIR). The analysis of audio signals plays a pivotal role in the process of music genre classification, facilitating the extraction of pertinent information from the frequency-based data of the auditory content. In this study, diverse acoustic characteristics were derived through the utilization of the librosa library, and subsequent classification procedures were executed employing machine learning algorithms. 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