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ESWA
2007
176views more  ESWA 2007»
13 years 7 months ago
Credit scoring with a data mining approach based on support vector machines
The credit card industry has been growing rapidly recently, and thus huge numbers of consumers’ credit data are collected by the credit department of the bank. The credit scorin...
Cheng-Lung Huang, Mu-Chen Chen, Chieh-Jen Wang
KAIS
2006
121views more  KAIS 2006»
13 years 7 months ago
Using discriminant analysis for multi-class classification: an experimental investigation
Abstract. Many supervised machine learning tasks can be cast as multi-class classification problems. Support vector machines (SVMs) excel at binary classification problems, but the...
Tao Li, Shenghuo Zhu, Mitsunori Ogihara
ICMLA
2003
13 years 9 months ago
Robust Support Vector Machines for Anomaly Detection in Computer Security
— Using the 1998 DARPA BSM data set collected at MIT’s Lincoln Labs to study intrusion detection systems, the performance of robust support vector machines (RVSMs) was compared...
Wenjie Hu, Yihua Liao, V. Rao Vemuri
GECCO
2007
Springer
184views Optimization» more  GECCO 2007»
13 years 11 months ago
Evolving kernels for support vector machine classification
While support vector machines (SVMs) have shown great promise in supervised classification problems, researchers have had to rely on expert domain knowledge when choosing the SVM&...
Keith Sullivan, Sean Luke
SIGKDD
2000
139views more  SIGKDD 2000»
13 years 7 months ago
Support Vector Machines: Hype or Hallelujah?
Support Vector Machines (SVMs) and related kernel methods have become increasingly popular tools for data mining tasks such as classification, regression, and novelty detection. T...
Kristin P. Bennett, Colin Campbell