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Overview: 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. Machine Learning has been an intensive research endeavor leading in recent years to a wealth of concepts, algorithms, and implementations encompassing a variety of original and far-reaching application domains. The successes of designed learning environments are highly impactful, especially in the realm of natural language processing (NLP) as well as image processing and computer vision. 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.
Genre: Non-Fiction > Tech & Devices
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