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KDD
2008
ACM
137views Data Mining» more  KDD 2008»
14 years 11 months ago
Learning classifiers from only positive and unlabeled data
The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...
Charles Elkan, Keith Noto
ICPR
2002
IEEE
15 years 2 days ago
Learning Bayesian Network Classifiers for Credit Scoring Using Markov Chain Monte Carlo Search
In this paper, we will evaluate the power and usefulness of Bayesian network classifiers for credit scoring. Various types of Bayesian network classifiers will be evaluated and co...
Bart Baesens, Michael Egmont-Petersen, Robert Cast...
GECCO
2007
Springer
213views Optimization» more  GECCO 2007»
14 years 5 months ago
Genetically programmed learning classifier system description and results
An agent population can be evolved in a complex environment to perform various tasks and optimize its job performance using Learning Classifier System (LCS) technology. Due to the...
Gregory Anthony Harrison, Eric W. Worden
ADMA
2006
Springer
153views Data Mining» more  ADMA 2006»
14 years 29 days 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
CEC
2005
IEEE
14 years 4 months ago
Revisiting genetic selection in the XCS learning classifier system
The XCS Learning Classifier System has traditionally used roulette wheel selection within its genetic algorithm component. Recently, tournament selection has been suggested as prov...
Faten Kharbat, Larry Bull, Mohammed Odeh