Abstract
Most supervised learning algorithms are either regression or classification procedures, depending on whether the desired system output is real-valued or binary-valued. Such algorithms belong to important techniques in machine learning, computational intelligence and data mining [137], [201]. Classification systems (classifiers for short) are used for solving the problems which arise in many fields including pattern recognition, vision analysis and other decision making purposes.
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© 2009 Springer-Verlag Berlin Heidelberg
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Kluska, J. (2009). Binary Classification Using P1-TS Rule Scheme. In: Analytical Methods in Fuzzy Modeling and Control. Studies in Fuzziness and Soft Computing, vol 241. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89927-3_7
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DOI: https://doi.org/10.1007/978-3-540-89927-3_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-89926-6
Online ISBN: 978-3-540-89927-3
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