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https://www.researchgate.net/publication/4116664_Extracting_the_knowledge_embedded_in_support_vector_machines
Request PDF Extracting the knowledge embedded in support vector machines One of the main challenges in support vector machine (SVM) for data mining applications is to obtain explicit knowledge ...
http://www.eng.tau.ac.il/~michaelm/shahaf.pdf
Knowledge Extraction from Support Vector Machines: A Fuzzy Logic Approach ... The knowledge embedded in the FARB is represented in a symbolic form, so this equivalence ... Extracting the knowledge learned by a black–box classifier and representing
https://pdfs.semanticscholar.org/3c77/d10b16f5e3d5dc3cf0bbd2817c966479f698.pdf
Keywords: Data mining, F-score, Genetic Algorithm, K-means, ReliefF, Support Vector Machines. I. INTRODUCTION Data mining is the process of representing the useful and meaningful data from very large volumes of data. It is also referred to as ‘knowledge mining’ i.e. to obtain knowledge from the data. Data mining gives solution to the
https://www.researchgate.net/publication/221138997_Symbolic_Knowledge_Extraction_from_Support_Vector_Machines_A_Geometric_Approach
The learning system relies on a support vector machine (SVM), meanwhile a rule extraction module translate the embedded knowledge in the trained SVM in the form of symbolic rules.
https://www.semanticscholar.org/paper/Rule-extraction-from-support-vector-machines-N%C3%BA%C3%B1ez-Angulo/1a129126a237c69cf110132f2742b55d82dae38f
Support vector machines (SVMs) are learning systems based on the statistical learning theory, which are exhibiting good generalization ability on real data sets. Nevertheless, a possible limitation of SVM is that they generate black box models. In this work, a procedure for rule extraction from support vector machines is proposed: the SVM+Prototypes method. This method allows to give ...
https://www.researchgate.net/publication/325442079_Rule-Extraction_from_Support_Vector_Machines
Over the last years, a number of studies on rule extraction from support vector machines (SVMs) have been introduced [1-5]. The research strategy in these projects is similar: to explore and ...
https://www.researchgate.net/publication/228744461_Linguistic_Rule_Extraction_from_Support_Vector_Machine_Classifiers
PDF Classification decisions from linguistic rules are more desirable compared to complex mathematical formulas from support vector machine (SVM)... Find, read and cite all the research you ...
https://rd.springer.com/chapter/10.1007/978-1-84996-098-4_4
Jan 22, 2010 · Abstract. Since the introduction of support vector machines, numerous variants have been developed. In this chapter, we discuss some of them: least-squares support vector machines, linear programming support vector machines, sparse support vector machines, etc.Cited by: 6
https://link.springer.com/article/10.1007/s00521-012-1048-5
Jul 10, 2012 · This paper proposes a new method for fuzzy rule extraction from trained support vector machines (SVMs) for multi-class problems, named FREx_SVM. SVMs have been used in a variety of applications. However, they are considered “black box models,” where no interpretation about the input–output mapping is provided. Some methods to reduce this limitation have already been …Cited by: 11
https://www.researchgate.net/publication/37617678_Knowledge_Initialisation_for_Support_Vector_Machines
Knowledge Initialisation for Support Vector Machines ... rule initialisation for support vector machines is presented. ... questions in extracting the knowledge embedded within ANN's including the ...
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