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ICPR
2006
IEEE
14 years 11 months ago
Rule Extraction from Support Vector Machines: Measuring the Explanation Capability Using the Area under the ROC Curve
Recently, the area of rule extraction from support vector machines (SVMs) has been explored. One important indication of the success of a rule extraction method is the performance...
Andrew P. Bradley, Nahla H. Barakat
ICPR
2004
IEEE
14 years 11 months ago
Signal Discrimination Using a Support Vector Machine for Genetic Syndrome Diagnosis
In this study, a support vector machine (SVM) classifies real world data of cytogenetic signals measured from fluorescence in-situ hybridization (FISH) images in order to diagnose...
Amit David, Boaz Lerner
ICPR
2000
IEEE
14 years 11 months ago
Data Condensation in Large Databases by Incremental Learning with Support Vector Machines
An algorithmfor data condensation using support vector machines (SVM's)is presented. The algorithm extracts datapoints lying close to the class boundaries,whichform a much re...
Pabitra Mitra, C. A. Murthy, Sankar K. Pal
ICML
2006
IEEE
14 years 11 months ago
Simpler knowledge-based support vector machines
If appropriately used, prior knowledge can significantly improve the predictive accuracy of learning algorithms or reduce the amount of training data needed. In this paper we intr...
Quoc V. Le, Alex J. Smola, Thomas Gärtner
ICML
2004
IEEE
14 years 11 months ago
Support vector machine learning for interdependent and structured output spaces
Learning general functional dependencies is one of the main goals in machine learning. Recent progress in kernel-based methods has focused on designing flexible and powerful input...
Ioannis Tsochantaridis, Thomas Hofmann, Thorsten J...