教師資料查詢 | 類別: 期刊論文 | 教師: 許輝煌 Hsu Hui-huang (瀏覽個人網頁)

標題:Feature Selection via Correlation Coefficient Clustering
學年99
學期1
出版(發表)日期2010/12/01
作品名稱Feature Selection via Correlation Coefficient Clustering
作品名稱(其他語言)
著者Hsu, Hui-Huang; Hsieh, Cheng-Wei
單位淡江大學資訊工程學系
出版者Oulu: Academy Publisher
著錄名稱、卷期、頁數Journal of Software 5(12), pp.1371-1377
摘要Feature selection is a fundamental problem in machine learning and data mining. How to choose the most problem-related features from a set of collected features is essential. In this paper, a novel method using correlation coefficient clustering in removing similar/redundant features is proposed. The collected features are grouped into clusters by measuring their correlation coefficient values. The most class-dependent feature in each cluster is retained while others in the same cluster are removed. Thus, the most class-related and mutually unrelated features are identified. The proposed method was applied to two datasets: the disordered protein dataset and the Arrhythmia (ARR) dataset. The experimental results show that the method is superior to other feature selection methods in speed and/or accuracy. Detail discussions are given in the paper.
關鍵字Feature Selection; Clustering; Correlation Coefficient; Support Vector Machines (SVMs); Machine Learning; Classification
語言英文
ISSN1796-217X
期刊性質國外
收錄於EI
產學合作
通訊作者Hsu, Hui-Huang; Hsieh, Cheng-Wei
審稿制度
國別芬蘭
公開徵稿
出版型式紙本
相關連結
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