A novel feature selection method and its application on the heart SPECT standard data

摘要：

Feature selection is used for finding a feature subset that has the most discriminative information from the original feature set. Large number of features often includes many garbage features. We propose a novel feature selection method on the basis of the estimation of Bayes discrimination boundary. The experimental results on heart Single Proton Emission Computed Tomography (SPECT) data shows the fundamental effectiveness of the proposed method compared to the conventional forward feature selection methods.

关键词： Feature selection Bayes classifier Bayes Boundary, Garbage feature removal Normal vector

作者: Azadeh Sadooghi Mohammad Mikaili

作者单位: Department of engineering Shahed University Tehran, Iran

会议类型: 国际会议

会议名称: The 2nd International Conference on Bioinformatics and Biomedical Engineering(iCBBE 2008)(第二届生物信息与生物医学工程国际会议)

会议地点: 上海

会议语种:英文

页码: 1880-1883

在线出版日期: 2008-05-16（万方平台首次上网日期，不代表论文的发表时间）