improving music mood classification using lyrics, audio and social tags
improving music mood classification using lyrics, audio and social tags
improving music mood classification using lyrics, audio and social tags
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4.3 SUMMARY<br />
This chapter described the design of <strong>classification</strong> experiments for answering research<br />
questions 2 to 5, as well as the rationale behind the design. The evaluation task is a binary<br />
<strong>classification</strong> where a <strong>classification</strong> model is built for each <strong>mood</strong> category. Accuracy will be<br />
used as the evaluation measure <strong>and</strong> performances on individual categories will be combined<br />
<strong>using</strong> macro-averaging so as to give equal weight to each category. A 10-fold cross validation<br />
evaluation will be employed for splitting training <strong>and</strong> testing datasets. The performances of<br />
different systems will be rigorously compared <strong>using</strong> Friedman’s ANOVA tests. The<br />
<strong>classification</strong> systems will be built <strong>using</strong> the SVM <strong>classification</strong> algorithm because of its superior<br />
performances in related <strong>classification</strong> tasks, <strong>and</strong> the LIBSVM software package will be used as<br />
the <strong>classification</strong> tool due to its popularity <strong>and</strong> flexibility.<br />
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