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126
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MLDM
2008
Springer
15 years 3 months ago
Classification Based on Consistent Itemset Rules
Abstract. We propose an approach to build a classifier composing consistent (100% confident) rules. Recently, associative classifiers that utilize association rules have been widel...
Yohji Shidara, Mineichi Kudo, Atsuyoshi Nakamura
164
Voted
GECCO
2011
Springer
236views Optimization» more  GECCO 2011»
14 years 7 months ago
Online, GA based mixture of experts: a probabilistic model of ucs
In recent years there have been efforts to develop a probabilistic framework to explain the workings of a Learning Classifier System. This direction of research has met with lim...
Narayanan Unny Edakunni, Gavin Brown, Tim Kovacs
118
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ADMA
2006
Springer
153views Data Mining» more  ADMA 2006»
15 years 5 months ago
An Effective Combination Based on Class-Wise Expertise of Diverse Classifiers for Predictive Toxicology Data Mining
This paper presents a study on the combination of different classifiers for toxicity prediction. Two combination operators for the Multiple-Classifier System definition are also pr...
Daniel Neagu, Gongde Guo, Shanshan Wang
136
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ICML
1996
IEEE
16 years 4 months ago
Sensitive Discount Optimality: Unifying Discounted and Average Reward Reinforcement Learning
Research in reinforcementlearning (RL)has thus far concentrated on two optimality criteria: the discounted framework, which has been very well-studied, and the averagereward frame...
Sridhar Mahadevan
CIA
2001
Springer
15 years 8 months ago
Wizard of Oz Method for Learning Dialog Agents
This paper describes a framework to construct interface agents with example dialogs based on the tasks by the machine learning technology. The Wizard of Oz method is used to collec...
Masayuki Okamoto, Yeonsoo Yang, Toru Ishida