计算机工程与应用2012，Vol.48Issue(6)：151-154,4.DOI:10.3778/j.issn.1002-8331.2012.06.044
基于半模糊核聚类算法的收视率预测研究
Study on audio rating prediction based on semi-fuzzy kernel clustering algorithm
陈青 1薛惠锋 1闫莉1
作者信息
- 1. 西北工业大学自动化学院,西安710072
- 折叠
摘要
Abstract
Audio rating is one of the most important indicators of TV industry, which is of great value to decision making of TV station. According to characters of more impact factors and complexity of variety, a new method of hyper-sphere Support Vector Machine (SVM) multi-class classification based on semi-fuzzy kernel clustering is proposed. The new method defines confusion classes based on semi-fuzzy kernel clustering and sphere support vector machines using the information from boundary so as to improve the performance of classifier efficiently. Experimental results indicate that the new method yields higher precision and speed than classical classification methods.关键词
收视率/半模糊聚类/支持向量机Key words
audio rating/semi-fuzzy cluster/Support Vector Machine(SVM)分类
信息技术与安全科学引用本文复制引用
陈青,薛惠锋,闫莉..基于半模糊核聚类算法的收视率预测研究[J].计算机工程与应用,2012,48(6):151-154,4.
