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This book facilitates both the theoretical background and
applications of fuzzy, intuitionistic fuzzy and rough, fuzzy rough
sets in the area of data science. This book provides various
individual, soft computing, optimization and hybridization
techniques of fuzzy and intuitionistic fuzzy sets with rough sets
and their applications including data handling and that of type-2
fuzzy systems. Machine learning techniques are effectively
implemented to solve a diversity of problems in pattern
recognition, data mining and bioinformatics. To handle different
nature of problems, including uncertainty, the book highlights the
theory and recent developments on uncertainty, fuzzy systems,
feature extraction, text categorization, multiscale modeling, soft
computing, machine learning, deep learning, SMOTE, data handling,
decision making, Diophantine fuzzy soft set, data envelopment
analysis, centrally measures, social networks, Volterra–Fredholm
integro-differential equation, Caputo fractional derivative,
interval optimization, decision making, classification problems.
This book is predominantly envisioned for researchers and students
of data science, medical scientists and professional engineers.
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