An instance-weighting method to induce cost-sensitive trees

IEEE Transactions on Knowledge and Data Engineering

Volumn 14, Issue 3, 2002, Pages 659-665

  Ting, Kai Ming ^a,b  

^a IEEE   (Australia)

^b UNIVERSITY OF BALLARAT   (Australia)

Author keywords

Cost sensitive; Decision trees; Greedy divide and conquer algorithm; Induction; Instance weighting

Indexed keywords

COST SENSITIVE TREES;

COST EFFECTIVENESS; DECISION THEORY; LEARNING ALGORITHMS; LEARNING SYSTEMS; TREES (MATHEMATICS);

DATABASE SYSTEMS;

EID: 0036565589     PISSN: 10414347     EISSN: None     Source Type: Journal    
DOI: 10.1109/TKDE.2002.1000348     Document Type: Article

References (17)

1. Pruning decision trees with misclassification costs
2. Cost-sensitive pruning of decision trees
3. Generating better decision trees
4. The use of background knowledge in decision tree induction
5. Reducing misclassification costs
6. Boosting, bagging, and C4.5
7. Boosting the margin: A new explanation for the effectiveness of voting methods
8. Cost-sensitive learning of classification knowledge and its applications in robotics
9. A comparative study of cost-sensitive boosting algorithms
10. Boosting cost-sensitive trees
11. Cost-sensitive classification: Empirical evaluation of a hybrid genetic decision tree induction algorithm
12. Cost-sensitive specialization