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» The Alternating Decision Tree Learning Algorithm
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CSDA
2006
91views more  CSDA 2006»
14 years 9 months ago
Maximum a posteriori pruning on decision trees and its application to bootstrap BUMPing
The cost-complexity pruning generates nested subtrees and selects the best one. However, its computational cost is large since it uses holdout sample or cross-validation. On the o...
Jinseog Kim, Yongdai Kim
ICANNGA
2007
Springer
161views Algorithms» more  ICANNGA 2007»
15 years 1 months ago
Evolutionary Induction of Decision Trees for Misclassification Cost Minimization
Abstract. In the paper, a new method of decision tree learning for costsensitive classification is presented. In contrast to the traditional greedy top-down inducer in the proposed...
Marek Kretowski, Marek Grzes
NLP
2000
15 years 1 months ago
Learning Rules for Large-Vocabulary Word Sense Disambiguation: A Comparison of Various Classifiers
In this article we compare the performance of various machine learning algorithms on the task of constructing word-sense disambiguation rules from data. The distinguishing characte...
Georgios Paliouras, Vangelis Karkaletsis, Ion Andr...
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ICML
2004
IEEE
15 years 10 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...
ICML
2006
IEEE
15 years 10 months ago
An empirical comparison of supervised learning algorithms
A number of supervised learning methods have been introduced in the last decade. Unfortunately, the last comprehensive empirical evaluation of supervised learning was the Statlog ...
Rich Caruana, Alexandru Niculescu-Mizil