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https://www.sciencedirect.com/science/article/pii/S0925231210001591
In this paper, we conduct a formal review of the area of rule extraction from SVMs. The review provides a historical perspective for this area of research and conceptually groups and analyzes the various techniques. In particular, we propose two alternative groupings; the first is based on the SVM (model) components utilized for rule extraction ...Cited by: 174
https://www.researchgate.net/publication/222256776_Rule_extraction_from_support_vector_machines_A_review
Rule extraction from support vector machines: A review. ... A review on the rule extraction and the main features of the algorithm from SVM can be seen in [5 ...
https://eprints.qut.edu.au/114212/
In this paper, we conduct a formal review of the area of rule extraction from SVMs. The review provides a historical perspective for this area of research and conceptually groups and analyzes the various techniques. ... Rule extraction from support vector machines: A review Barakat, N. & Bradley, A. P. (2010) Rule extraction from support vector ...Cited by: 174
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 ...Author: Joachim Diederich
https://link.springer.com/chapter/10.1007%2F978-3-540-75390-2_1
Rule extraction from support vector machines (SVMs) follows in the footsteps of the earlier effort to obtain human-comprehensible rules from artificial neural networks (ANNs) in order to explain “how” a decision was made or “why” a certain result was achieved.Cited by: 23
https://dl.acm.org/citation.cfm?id=1891195
N. Barakat, J. Diederich, Learning-based rule-extraction from support vector machines: performance on benchmark data sets, in: Proceedings of the Conference on Neuro-Computing and Evolving Intelligence, Knowledge Engineering and Discovery Research …Cited by: 174
https://issuu.com/bellearmstrong/docs/rule_extraction_from_support_vector_machine.pdf
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https://www.elen.ucl.ac.be/Proceedings/esann/esannpdf/es2002-51.pdf
Rule extraction from support vector machines Haydemar Núñez1,3 Cecilio Angulo1,2 Andreu Català1,2 1Dept. of Systems Engineering, Polytechnical University of Catalonia Avda. Victor Balaguer s/n E-08800 Vilanova i la Geltrú, Spain {hnunez,cangulo}@esaii.upc.es
https://www.sciencedirect.com/science/article/pii/S0924271610001140
A wide range of methods for analysis of airborne- and satellite-derived imagery continues to be proposed and assessed. In this paper, we review remote sensing implementations of support vector machines (SVMs), a promising machine learning methodology.Cited by: 1798
https://link.springer.com/chapter/10.1007/978-3-319-19222-2_23
Jun 06, 2015 · Abstract. Rule extraction from neural networks represents a difficult research problem, which is NP-hard. In this work we show how a special Multi Layer Perceptron architecture denoted as DIMLP can be used to extract rules from ensembles of DIMLPs and Quantized Support Vector Machines (QSVMs).Cited by: 6
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