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» Data selection for support vector machine classifiers
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KDD
2000
ACM
133views Data Mining» more  KDD 2000»
13 years 8 months ago
Data selection for support vector machine classifiers
The problem of extracting a minimal number of data points from a large dataset, in order to generate a support vector machine (SVM) classifier, is formulated as a concave minimiza...
Glenn Fung, Olvi L. Mangasarian
IJCNN
2006
IEEE
13 years 10 months ago
Classify Unexpected News Impacts to Stock Price by Incorporating Time Series Analysis into Support Vector Machine
— the paper discusses an approach of using traditional time series analysis, as domain knowledge, to help the data-preparation of support vector machine for classifying documents...
Ting Yu, Tony Jan, John K. Debenham, Simeon J. Sim...
KDD
2002
ACM
160views Data Mining» more  KDD 2002»
14 years 5 months ago
Scaling multi-class support vector machines using inter-class confusion
Support vector machines (SVMs) excel at two-class discriminative learning problems. They often outperform generative classifiers, especially those that use inaccurate generative m...
Shantanu Godbole, Sunita Sarawagi, Soumen Chakraba...
CDC
2009
IEEE
126views Control Systems» more  CDC 2009»
13 years 5 months ago
Support vector machine classifiers for sequential decision problems
Classification problems in critical applications such as health care or security often require very high reliability because of the high costs of errors. In order to achieve this r...
Eladio Rodriguez Diaz, David A. Castaon
JMLR
2008
110views more  JMLR 2008»
13 years 4 months ago
Estimating the Confidence Interval for Prediction Errors of Support Vector Machine Classifiers
Support vector machine (SVM) is one of the most popular and promising classification algorithms. After a classification rule is constructed via the SVM, it is essential to evaluat...
Bo Jiang, Xuegong Zhang, Tianxi Cai