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Fuzzy rough sets and fuzzy rough neural networks for feature selection: A review
Feature selection aims to select a feature subset from an original feature set based on a
certain evaluation criterion. Since feature selection can achieve efficient feature reduction, it …
certain evaluation criterion. Since feature selection can achieve efficient feature reduction, it …
Applications of fuzzy rough set theory in machine learning: a survey
Data used in machine learning applications is prone to contain both vague and incomplete
information. Many authors have proposed to use fuzzy rough set theory in the development …
information. Many authors have proposed to use fuzzy rough set theory in the development …
[ספר][B] Dealing with imbalanced and weakly labelled data in machine learning using fuzzy and rough set methods
S Vluymans - 2019 - Springer
This book is based on my Ph. D. dissertation completed at Ghent University (Belgium) and
the University of Granada (Spain) in June 2018. It focuses on classification. The goal is to …
the University of Granada (Spain) in June 2018. It focuses on classification. The goal is to …
Fuzzy rough granular self-organizing map and fuzzy rough entropy
A fuzzy rough granular self-organizing map (FRGSOM) involving a 3-dimensional linguistic
vector and connection weights, defined in an unsupervised manner, is proposed for …
vector and connection weights, defined in an unsupervised manner, is proposed for …
Introduction to granular computing, pattern recognition and data mining
Natural Computing is a consortium of different methods and theories that are emerged from
natural phenomena such as brain modeling, self-organization, self-repetition, self …
natural phenomena such as brain modeling, self-organization, self-repetition, self …