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      A Novel Hybrid Grey Wolf Optimization Algorithm Using Two-Phase Crossover Approach for Feature Selection and Classification

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          Abstract

          Abstract: Data mining process can be hampered by high dimensional large datasets, so feature selection become a mandatory task in prior for dimensionality reduction of datasets. Main motive of feature selection process is to choose most informative features and use them to maximize the classification accuracy. This work introduces a novel two phase crossover operator with grey wolf algorithm to solve the problem of feature selection. Two phase crossover improves the exploitation part. First phase crossover is used for feature selection and second phase used for adding some more important information and improve the classification accuracy. The KNN classifier improved the classification accuracy which is most famous classifier based on wrapper method. Ten-fold crossover validation is used to defeat the over-fitting problem which is always a milestone in the way of accuracy. Experiments are applied using various datasets and results prove that proposed algorithm outperform and provide better results.

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          Most cited references19

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          Grey Wolf Optimizer

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            Binary grey wolf optimization approaches for feature selection

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              Binary Grasshopper Optimisation Algorithm Approaches for Feature Selection Problems

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                Author and article information

                Journal
                cys
                Computación y Sistemas
                Comp. y Sist.
                Instituto Politécnico Nacional, Centro de Investigación en Computación (Ciudad de México, Ciudad de México, Mexico )
                1405-5546
                2007-9737
                December 2021
                : 25
                : 4
                : 793-801
                Affiliations
                [1] Guru Jambheshwar orgnameUniversity of Science and Technology India jyoti.vst@ 123456gmail.com
                Article
                S1405-55462021000400793 S1405-5546(21)02500400793
                10.13053/cys-25-4-3931
                61e73ccc-bc82-4149-a667-38ef17a8975f

                This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

                History
                : 15 August 2021
                : 08 April 2021
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 27, Pages: 9
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                SciELO Mexico

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                Articles

                KNN (K-Nearest neighbor),ALO (Ant Lion algorithm),BGOA (binary grasshopper approach),FS (feature selection),GWO (Grey Wolf Optimization),PSO (Particle Swarm Optimization),TCGWO (Two-Phase Crossover Grey Wolf Optimization),WOA (Whale Optimization algorithm)

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