  Scientists have used many different classification methods to solve the
problem of music classification. But the efficiency of each classification is
different. In this paper, we propose two compared methods on the task of music
style classification. More specifically, feature extraction for representing
timbral texture, rhythmic content and pitch content are proposed. Comparative
evaluations on performances of two classifiers were conducted for music
classification with different styles. The result shows that XGB is better
suited for small datasets than BPNN
