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» Rule extraction from linear support vector machines
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KDD
2005
ACM
117views Data Mining» more  KDD 2005»
14 years 5 months ago
Rule extraction from linear support vector machines
We describe an algorithm for converting linear support vector machines and any other arbitrary hyperplane-based linear classifiers into a set of non-overlapping rules that, unlike...
Glenn Fung, Sathyakama Sandilya, R. Bharat Rao
EOR
2007
101views more  EOR 2007»
13 years 4 months ago
Comprehensible credit scoring models using rule extraction from support vector machines
In recent years, Support Vector Machines (SVMs) were successfully applied to a wide range of applications. Their good performance is achieved by an implicit non-linear transformat...
David Martens, Bart Baesens, Tony Van Gestel, Jan ...
ICPR
2006
IEEE
14 years 5 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
FSS
2007
102views more  FSS 2007»
13 years 4 months ago
Extraction of fuzzy rules from support vector machines
The relationship between support vector machines (SVMs) and Takagi–Sugeno–Kang (TSK) fuzzy systems is shown. An exact representation of SVMs as TSK fuzzy systems is given for ...
Juan Luis Castro, L. D. Flores-Hidalgo, Carlos Jav...
ICMCS
2005
IEEE
229views Multimedia» more  ICMCS 2005»
13 years 10 months ago
A methodology for improving recognition rate of linear discriminant analysis in video-based face recognition using support vecto
This paper proposes a two-step methodology for improving the discriminatory power of Linear Discriminant Analysis (LDA) for video-based human face recognition. Results indicate th...
Sreekar Krishna, Sethuraman Panchanathan