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PKDD
2005
Springer
167views Data Mining» more  PKDD 2005»
13 years 10 months ago
Hybrid Cost-Sensitive Decision Tree
Cost-sensitive decision tree and cost-sensitive naïve Bayes are both new cost-sensitive learning models proposed recently to minimize the total cost of test and misclassifications...
Shengli Sheng, Charles X. Ling
ECML
2006
Springer
13 years 8 months ago
Cost-Sensitive Decision Tree Learning for Forensic Classification
Abstract. In some learning settings, the cost of acquiring features for classification must be paid up front, before the classifier is evaluated. In this paper, we introduce the fo...
Jason V. Davis, Jungwoo Ha, Christopher J. Rossbac...
ECML
2005
Springer
13 years 10 months ago
Simple Test Strategies for Cost-Sensitive Decision Trees
We study cost-sensitive learning of decision trees that incorporate both test costs and misclassification costs. In particular, we first propose a lazy decision tree learning that ...
Shengli Sheng, Charles X. Ling, Qiang Yang
AAAI
2006
13 years 6 months ago
Cost-Sensitive Test Strategies
In medical diagnosis doctors must often determine what medical tests (e.g., X-ray, blood tests) should be ordered for a patient to minimize the total cost of medical tests and mis...
Shengli Sheng, Charles X. Ling, Ailing Ni, Shichao...
ICML
2000
IEEE
14 years 5 months ago
Exploiting the Cost (In)sensitivity of Decision Tree Splitting Criteria
This paper investigates how the splitting criteria and pruning methods of decision tree learning algorithms are influenced by misclassification costs or changes to the class distr...
Chris Drummond, Robert C. Holte