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Fuzzy, Rough and Intuitionistic Fuzzy Set Approaches for Data Handling
Tanmoy Som (Hrsg.), Shivam Shreevastava (Hrsg.), Anoop Kumar Tiwari (Hrsg.), Oscar Castillo (Hrsg.)
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Naturwissenschaften, Medizin, Informatik, Technik / Informatik
Beschreibung
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.
Kundenbewertungen
machine learning, SMOTE, Interval optimization, multiscale modelling, data handling, text categorization, Volterra–Fredholm integro-differential equation, centrally measures, social networks, decision making, Diophantine fuzzy soft set, deep learning, Caputo fractional derivatives, soft computing, data envelopment analysis, uncertainty principle, intuitionistic fuzzy, fuzzy rough, feature extension, fuzzy systems