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FLAIRS
2008
15 years 1 months ago
Selecting Minority Examples from Misclassified Data for Over-Sampling
We introduce a method to deal with the problem of learning from imbalanced data sets, where examples of one class significantly outnumber examples of other classes. Our method sel...
Jorge de la Calleja, Olac Fuentes, Jesús Go...
116
Voted
GPEM
2010
134views more  GPEM 2010»
14 years 9 months ago
An ensemble-based evolutionary framework for coping with distributed intrusion detection
A distributed data mining algorithm to improve the detection accuracy when classifying malicious or unauthorized network activity is presented. The algorithm is based on genetic p...
Gianluigi Folino, Clara Pizzuti, Giandomenico Spez...
83
Voted
IJCNN
2006
IEEE
15 years 5 months ago
Predicting Juvenile Diabetes from Clinical Test Results
—Two approaches to building models for prediction of the onset of Type 1 diabetes mellitus in juvenile subjects were examined. A set of tests performed immediately before diagnos...
Shibendra S. Pobi, Lawrence O. Hall
IWDC
2004
Springer
120views Communications» more  IWDC 2004»
15 years 4 months ago
SCIDS: A Soft Computing Intrusion Detection System
An Intrusion Detection System (IDS) is a program that analyzes what happens or has happened during an execution and tries to find indications that the computer has been misused. Th...
Ajith Abraham, Ravi Jain, Sugata Sanyal, Sang-Yong...
73
Voted
ICML
2005
IEEE
15 years 12 months ago
Recycling data for multi-agent learning
Learning agents can improve performance cooperating with other agents, particularly learning agents forming a committee outperform individual agents. This "ensemble effect&qu...
Santiago Ontañón, Enric Plaza