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ICML
2000
IEEE
14 years 8 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
ICML
2004
IEEE
14 years 8 months ago
Decision trees with minimal costs
We propose a simple, novel and yet effective method for building and testing decision trees that minimizes the sum of the misclassification and test costs. More specifically, we f...
Charles X. Ling, Qiang Yang, Jianning Wang, Shicha...
JMLR
2010
125views more  JMLR 2010»
13 years 2 months ago
Maximum Likelihood in Cost-Sensitive Learning: Model Specification, Approximations, and Upper Bounds
The presence of asymmetry in the misclassification costs or class prevalences is a common occurrence in the pattern classification domain. While much interest has been devoted to ...
Jacek P. Dmochowski, Paul Sajda, Lucas C. Parra
PRL
2006
89views more  PRL 2006»
13 years 7 months ago
ROC graphs with instance-varying costs
Receiver Operating Characteristics (ROC) graphs are a useful technique for organizing classifiers and visualizing their performance. ROC graphs have been used in cost-sensitive le...
Tom Fawcett
KDD
1998
ACM
120views Data Mining» more  KDD 1998»
13 years 11 months ago
Ranking - Methods for Flexible Evaluation and Efficient Comparison of Classification Performance
We present the notion of Ranking for evaluation of two-class classifiers. Ranking is based on using the ordering information contained in the output of a scoring model, rather tha...
Saharon Rosset