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Granular computing

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Granular computing

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Granular computing --- GC (Computer science) --- Soft computing

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A comprehensive coverage of emerging and current technology dealing with heterogeneous sources of information, including data, design hints, reinforcement signals from external datasets, and related topicsCovers all necessary prerequisites, and if necessary,additional explanations of more advanced topics, to make abstract concepts more tangibleIncludes illustrative material andwell-known experimentsto offer hands-on experience

Soft computing. --- Granular computing. --- Fuzzy systems.

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Pattern Recognition Algorithms for Data Mining addresses pattern recognition (PR) tasks in a unified framework with both theoretical and experimental results. Tasks covered include data condensation, feature selection, case generation, clustering/classification, and rule generation and evaluation. Organized into eight chapters, the book begins by introducing PR, data mining, and knowledge discovery concepts. The authors proceed to analyze the tasks of multi-scale data condensation and dimensionality reduction. Then they explore the problem of learning with support vector machine (SVM), and conclude by highlighting the significance of granular computing for different mining tasks in a soft paradigm.

Computer algorithms. --- Data mining. --- Granular computing. --- Pattern recognition systems. --- Acqui 2006 --- Data mining --- Pattern recognition systems --- Computer algorithms --- Granular computing