教師資料查詢 | 類別: 期刊論文 | 教師: 倪衍森NI, YEN-SEN (瀏覽個人網頁)

標題:基於類-屬性關聯度的啟發式離散化技術
學年100
學期1
出版(發表)日期2011/10/01
作品名稱基於類-屬性關聯度的啟發式離散化技術
作品名稱(其他語言)Heuristic discretization technique based on the class-attribute interdependence
著者周世昊; 倪衍森
單位淡江大學管理科學學系
出版者瀋陽市:東北大學
著錄名稱、卷期、頁數控制與決策=Control and Decision 26(10),頁1504-1510
摘要Discretization algorithms play an important role in many areas such as data mining, machine learning and artificial intelligence. Therefore, a heuristic discretization technique based on the class-attribute interdependence is proposed. A new discretization criterion is defined, which selects best cut points in terms of characteristics of the data itself and overcomes the existing deficiencies of state-of-the-art top-down discretization methods. A novel measure of inconsistency based on variable precision rough sets(VPRS) model is developed, which effectively controls information loss generated by discretization and allows an adaptive degree of misclassification. Empirical experiments and statistical analysis show that the proposed technique generates a better discretization scheme which significantly improves the accuracy of classification by running J4.8 and SVM.
關鍵字離散化; 數據挖掘; 自頂向下; 變精度粗糙集; 不一致; discretization; data mining; top-down; variable precision rough sets; inconsistency
語言中文簡體
ISSN1001-0920
期刊性質國外
收錄於EI
產學合作
通訊作者
審稿制度
國別中國
公開徵稿
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