教師資料查詢 | 類別: 期刊論文 | 教師: 吳家齊 WU, CHIA-CHI (瀏覽個人網頁)

標題:Cost-sensitive decision tree with multiple resource constraints
學年108
學期1
出版(發表)日期2019/10/01
作品名稱Cost-sensitive decision tree with multiple resource constraints
作品名稱(其他語言)
著者Chia-Chi Wu; Yen-Liang Chen; Kwei Tang
單位
出版者
著錄名稱、卷期、頁數Applied Intelligence 49, p.3765-3782
摘要Measuring an attribute may consume several types of resources. For example, a blood test has a cost and needs to wait for a result. Resource constraints are often imposed on a classification task. In medical diagnosis and marketing campaigns, it is common to have a deadline and budget for finishing the task. The objective of this paper is to develop an algorithm for inducing a classification tree with minimal misclassification cost under multiple resource constraints. To our best knowledge, the problem has not been studied in the literature. To address this problem, we propose an innovative algorithm, namely, the Cost-Sensitive Associative Tree (CAT) algorithm. Essentially, the algorithm first extracts and retains association classification rules from the training data which satisfy resource constraints, and then uses the rules to construct the final decision tree. The approach can ensure that the classification task is done within the specified resource constraints. The experiment results show that the CAT algorithm significantly outperforms the traditional top-down approach and adapts very well to available resources.
關鍵字Data mining;Machine Learning;Decision tree;Cost-sensitive learning
語言英文(美國)
ISSN1573-7497
期刊性質國外
收錄於SCI;
產學合作
通訊作者
審稿制度
國別美國
公開徵稿
出版型式,電子版,紙本
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