Enhanced Binary Cuckoo Search With Frequent Values and Rough Set Theory for Feature Selection

Enhanced Binary Cuckoo Search With Frequent Values and Rough Set Theory for Feature Selection

Redundant and irrelevant features in datasets decrease classification accuracy, and increase computational time of classification algorithms, overfitting problem and complexity of the underlying classification model. Feature selection is a preprocessing technique used in classification algorithms to...

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Bibliographic Details
Main Authors: Ahmed Alia, Adel Taweel
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Feature selection
classification
machine learning
rough set theory
enhanced binary cuckoo search
nature inspired algorithms
Online Access:https://ieeexplore.ieee.org/document/9522132/

Internet

https://ieeexplore.ieee.org/document/9522132/

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