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GECCO
2007
Springer
558views Optimization» more  GECCO 2007»
14 years 1 months ago
A chain-model genetic algorithm for Bayesian network structure learning
Bayesian Networks are today used in various fields and domains due to their inherent ability to deal with uncertainty. Learning Bayesian Networks, however is an NP-Hard task [7]....
Ratiba Kabli, Frank Herrmann, John McCall
GECCO
2009
Springer
109views Optimization» more  GECCO 2009»
13 years 12 months ago
A genetic algorithm for learning significant phrase patterns in radiology reports
Radiologists disagree with each other over the characteristics and features of what constitutes a normal mammogram and the terminology to use in the associated radiology report. R...
Robert M. Patton, Thomas E. Potok, Barbara G. Beck...
JIKM
2006
136views more  JIKM 2006»
13 years 7 months ago
Decision Support Systems Using Ensemble Genetic Programming
Abstract. This paper proposes a decision support system for tactical air combat environment using a combination of unsupervised learning for clustering the data and an ensemble of ...
Ajith Abraham, Crina Grosan
ICTAI
2006
IEEE
14 years 1 months ago
MI-Winnow: A New Multiple-Instance Learning Algorithm
We present MI-Winnow, a new multiple-instance learning (MIL) algorithm that provides a new technique to convert MIL data into standard supervised data. In MIL each example is a co...
Sharath R. Cholleti, Sally A. Goldman, Rouhollah R...
ITCC
2005
IEEE
14 years 28 days ago
Real Stock Trading Using Soft Computing Models
The main focus of this study is to compare different performances of soft computing paradigms for predicting the direction of individuals stocks. Three different artificial intell...
Brent Doeksen, Ajith Abraham, Johnson P. Thomas, M...