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» Results of the KDD'99 Classifier Learning
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GECCO
2007
Springer
210views Optimization» more  GECCO 2007»
14 years 1 months ago
Mining breast cancer data with XCS
In this paper, we describe the use of a modern learning classifier system to a data mining task. In particular, in collaboration with a medical specialist, we apply XCS to a prima...
Faten Kharbat, Larry Bull, Mohammed Odeh
ESANN
2008
13 years 9 months ago
An emphasized target smoothing procedure to improve MLP classifiers performance
Standard learning procedures are better fitted to estimation than to classification problems, and focusing the training on appropriate samples provides performance advantages in cl...
Soufiane El Jelali, Abdelouahid Lyhyaoui, An&iacut...
MICCAI
2008
Springer
14 years 9 months ago
Cortical Surface Thickness as a Classifier: Boosting for Autism Classification
We study the problem of classifying an autistic group from controls using structural image data alone, a task that requires a clinical interview with a psychologist. Because of the...
Vikas Singh, Lopamudra Mukherjee, Moo K. Chung
FLAIRS
2004
13 years 9 months ago
Prototype Based Classifier Design with Pruning
An algorithm is proposed to prune the prototype vectors (prototype selection) used in a nearest neighbor classifier so that a compact classifier can be obtained with similar or ev...
Jiang Li, Michael T. Manry, Changhua Yu
PRL
2006
146views more  PRL 2006»
13 years 7 months ago
Boosting the distance estimation: Application to the K-Nearest Neighbor Classifier
In this work we introduce a new distance estimation technique by boosting and we apply it to the K-Nearest Neighbor Classifier (KNN). Instead of applying AdaBoost to a typical cla...
Jaume Amores, Nicu Sebe, Petia Radeva