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DAWAK
2006
Springer
14 years 14 days ago
Mixed Decision Trees: An Evolutionary Approach
In the paper, a new evolutionary algorithm (EA) for mixed tree learning is proposed. In non-terminal nodes of a mixed decision tree different types of tests can be placed, ranging ...
Marek Kretowski, Marek Grzes
ML
2000
ACM
154views Machine Learning» more  ML 2000»
13 years 8 months ago
Lazy Learning of Bayesian Rules
The naive Bayesian classifier provides a simple and effective approach to classifier learning, but its attribute independence assumption is often violated in the real world. A numb...
Zijian Zheng, Geoffrey I. Webb
ECML
2006
Springer
14 years 14 days 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...
ICTAI
1999
IEEE
14 years 1 months ago
Controlled Flux Results in Stable Decision Trees
This work deals with stability in incremental induction of decision trees. Stability problems arise when an induction algorithm must revise a decision tree very often and oscillat...
Dimitrios Kalles, Athanassios Papagelis
ICML
1998
IEEE
14 years 9 months ago
A Fast, Bottom-Up Decision Tree Pruning Algorithm with Near-Optimal Generalization
In this work, we present a new bottom-up algorithmfor decision tree pruning that is very e cient requiring only a single pass through the given tree, and prove a strong performanc...
Michael J. Kearns, Yishay Mansour