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Learning and Soft Computing: Support Vector Machines, Neural Networks, and Fuzzy Logic Models by Vojislav Kecman

Learning and Soft Computing: Support Vector Machines, Neural Networks, and Fuzzy Logic Models Vojislav Kecman ebook
Format: pdf
Publisher: The MIT Press
Page: 576
ISBN: 0262112558, 9780262112550

Vojislav Kecman, "Learning and Soft Computing: Support Vector Machines, Neural Networks, and Fuzzy Logic Models (Complex Adaptive Systems)". The MIT Press | 2001-03-19 | ISBN: 0262112558 | 608 pages | DJVU | 7.1 MB. PdfLearning And Soft Computing - Support Vector Machines, Neural Networks, And Fuzzy Logic Models (2001).pdfKluwer Academic Publishers Flexible Neuro-fuzzy Systems Structures, Learning and Performance Evaluation. Learning And Soft Computing - Support Vector Machines, Neural Networks, And Fuzzy Logic Models - Vojislav Kecman.pdf. 12th EANN / 7th AIAI Joint Congress 2011 : 12th (IEEE-INNS) Engineering Applications of Neural Networks / 7th (IFIP) Artificial Intelligence Applications and Innovations. In effect, the role model for Soft computing is the human mind. The model produced by support vector classification (as described above) only depends on a subset of the training data, because the cost function for building the model does not care about training points that lie beyond the margin. KECMAN Vojislav (2001), Learning and Soft Computing, Support Vector Machines, Neural Networks and Fuzzy Logic Models, The MIT Press, Cambridge, MA, 608 pp., 268 illus., ISBN 0-262-11255-8. Patrick Blackburn, Johan Bos , Kristina Striegnitz.pdf. Thorough introduction to the field of learning from experimental data and soft computing. The principal constituents, i.e., tools, techniques, of Soft Computing (SC) are – Fuzzy Logic (FL), Neural Networks (NN), Support Vector Machines (SVM), Evolutionary Computation ( EC), and – Machine Learning (ML) and Probabilistic Reasoning (PR). Learning and Soft Computing: Support Vector Machines, Neural Networks, and Fuzzy Logic Models by Vojislav Kecman.