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Machine Learning and Granular Computing

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Machine Learning and Granular Computing Synopsis

This volume provides the reader with a comprehensive and up-to-date treatise positioned at the junction of the areas of Machine Learning (ML) and Granular Computing (GrC). ML offers a wealth of architectures and learning methods. Granular Computing addresses useful aspects of abstraction and knowledge representation that are of importance in the advanced design of ML architectures. In unison, ML and GrC support advances of the fundamental learning paradigm. As built upon synergy, this unified environment focuses on a spectrum of methodological and algorithmic issues, discusses implementations and elaborates on applications. The chapters bring forward recent developments showing ways of designing synergistic and coherently structured ML-GrC environment. The book will be of interest to a broad audience including researchers and practitioners active in the area of ML or GrC and interested in following its timely trends and new pursuits.

About This Edition

ISBN: 9783031668418
Publication date:
Author: Witold Pedrycz, ShyiMing Chen
Publisher: Springer an imprint of Springer Nature Switzerland
Format: Hardback
Pagination: 352 pages
Series: Studies in Big Data
Genres: Databases
Machine learning
Artificial intelligence

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