Neuro-Swarm Techniques for Classifier Design
Concepts, Models, Methods and Algorithms
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Since last few decades, the wide use of advanced technologies made massive growth in the availability of data from different resources, which lead to the challenge of extracting useful knowledge for specific applications. Classification is one of the most important tasks in mining knowledge from such resources. Though a wide number of traditional techniques are available for classification, but finding a high performance robust classification method, applicable to different real world problem is difficult. This book provides a set of techniques for classification which has been applied to prob...
Since last few decades, the wide use of advanced technologies made massive growth in the availability of data from different resources, which lead to the challenge of extracting useful knowledge for specific applications. Classification is one of the most important tasks in mining knowledge from such resources. Though a wide number of traditional techniques are available for classification, but finding a high performance robust classification method, applicable to different real world problem is difficult. This book provides a set of techniques for classification which has been applied to problems from multiple disciplines such as life science, physical science, social science, business, and games. Design of a wide range of classifiers using Polynomial Neural Network and its hybridization with Particle Swam Optimization, Fuzzy logic, Artificial Neural Network has been presented in this book with their scope and limitations. The algorithms and models presented for the large range of classifiers will certainly help the readers in using it conveniently for their application areas.
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