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This book provides a uniform framework describing how fuzzy rough granular neural network technologies can be formulated and used in building efficient pattern recognition and mining models.
This valuable text addresses different 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.
Addresses different pattern recognition (PR) tasks in a unified framework with both theoretical and experimental results. Organized into eight chapters, the book begins by introducing PR, data mining, and knowledge discovery concepts. It concludes by highlighting the significance of granular computing for different mining tasks in a soft paradigm.
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