计算机工程与应用2016，Vol.52Issue(6)：127-133,7.DOI:10.3778/j.issn.1002-8331.1405-0097
基于SVM主动学习的音乐分类
Music classification based on SVM active learning
摘要
Abstract
An improved SVM(Support Vector Machine)active learning method is proposed. By providing the user with the most informative samples which are put into training set through several iterations, the cost of manually labelled samples can be greatly reduced. In the experiment, to evaluate the performance of the classifier, it classifies 801 songs according to five kinds of genres(including dance, lyric, jazz, folk, rock), and verifies the effectiveness of SVM active learning in two aspects which are the accuracy convergence rate and the number of samples need to be labelled to achieve the same accuracy.关键词
支持向量机/主动学习/音乐分类Key words
Support Vector Machine(SVM)/active learning/music classification分类
信息技术与安全科学引用本文复制引用
邵曦,姚磊..基于SVM主动学习的音乐分类[J].计算机工程与应用,2016,52(6):127-133,7.基金项目
国家自然科学基金（No.60902065）。 （）
