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" Interpretability issues in fuzzy modeling "
J. Casillas [and others], eds.
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BL
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| Record Number
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745847
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b565796
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| Main Entry
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J. Casillas [and others], eds.
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| Title & Author
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Interpretability issues in fuzzy modeling\ J. Casillas [and others], eds.
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| Publication Statement
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Berlin ; New York : Springer, ©2003.
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| Series Statement
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Studies in fuzziness and soft computing, v. 128.
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(xiv, 643 pages) : illustrations
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| ISBN
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3540370579
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: 3642057020
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: 9783540370574
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: 9783642057021
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| Contents
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Overview --; Improving the Interpretability with Flexible Rule Stucture --; Complexity Reduction in Linguistic Fuzzy Models --; Complexity Reduction in Precise Fuzzy Models --; Interpretability Constraints in TSK Fuzzy Rule-Based Systems --; Assessments on the Interpretability Loss --; Interpretation of Black-Box Models as Fuzzy Rule-Based Models.
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| Abstract
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Fuzzy modeling has become one of the most productive and successful results of fuzzy logic. Among others, it has been applied to knowledge discovery, automatic classification, long-term prediction, or medical and engineering analysis. The research developed in the topic during the last two decades has been mainly focused on exploiting the fuzzy model flexibility to obtain the highest accuracy. This approach usually sets aside the interpretability of the obtained models. However, we should remember the initial philosophy of fuzzy sets theory directed to serve the bridge between the human understanding and the machine processing. In this challenge, the ability of fuzzy models to express the behavior of the real system in a comprehensible manner acquires a great importance. This book collects the works of a group of experts in the field that advocate the interpretability improvements as a mechanism to obtain well balanced fuzzy models.
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Fuzzy systems.
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Intelligent control systems.
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Soft computing.
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| LC Classification
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TJ217.5J337 2003
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| Added Entry
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J Casillas
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