A proposal for evolutionary fuzzy systems using feature weighting: Dealing with overlapping in imbalanced datasets-Reference-Cited by-同舟云学术

A proposal for evolutionary fuzzy systems using feature weighting: Dealing with overlapping in imbalanced datasets

Published:2015-01 Issue: Volume:73 Page:1-17
ISSN:0950-7051
Container-title:Knowledge-Based Systems
language:en
Short-container-title:Knowledge-Based Systems

Author:

Alshomrani Saleh,Bawakid Abdullah,Shim Seong-O,Fernández Alberto,Herrera Francisco

Funder

King Abdulaziz University

Spanish Ministry of Science and Technology

Andalusian Research Plans

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Management Information Systems,Software

Reference61 articles.

1. A fuzzy association rule-based classification model for high-dimensional problems with genetic rule selection and lateral tuning;Alcalá-Fdez;IEEE Trans. Fuzzy Syst.,2011

2. KEEL data-mining software tool: data set repository, integration of algorithms and experimental analysis framework;Alcalá-Fdez;J. Multi-Valued Logic Soft Comput.,2011

3. KEEL: a software tool to assess evolutionary algorithms for data mining problems;Alcalá-Fdez;Soft. Comput.,2009

4. Strategies for learning in class imbalance problems;Barandela;Pattern Recogn.,2003

5. A study of the behaviour of several methods for balancing machine learning training data;Batista;SIGKDD Explor.,2004

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