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  1. 1
    Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study

    Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study by Li Yu Yab, Li Yu Yab, Wahid, Noorhaniza, A Hamid, Rahayu

    Published 2023
    “…Therefore, to overcome this issue, a modified WOA (mWOA) and modified GWO (mGWO) for wrapper-based feature selection were proposed in this study. …”
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  2. 2
    Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study

    Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study by Li Yu Yab, Li Yu Yab, Wahid, Noorhaniza, A Hamid, Rahayu

    Published 2023
    “…Therefore, to overcome this issue, a modified WOA (mWOA) and modified GWO (mGWO) for wrapper-based feature selection were proposed in this study. …”
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  3. 3
    Aco-based feature selection algorithm for classification

    Aco-based feature selection algorithm for classification by Al-mazini, Hassan Fouad Abbas

    Published 2022
    “…The modified graph clustering ant colony optimisation (MGCACO) algorithm is an effective FS method that was developed based on grouping the highly correlated features. …”
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  4. 4
    An ensemble learning method for spam email detection system based on metaheuristic algorithms

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…In order to address the challenges that mentioned above in this study, in the first phase, a novel architecture based on ensemble feature selection techniques include Modified Binary Bat Algorithm (NBBA), Binary Quantum Particle Swarm Optimization (QBPSO) Algorithm and Binary Quantum Gravita tional Search Algorithm (QBGSA) is hybridized with the Multi-layer Perceptron (MLP) classifier in order to select relevant feature subsets and improve classification accuracy. …”
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  5. 5
    Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection

    Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection by Almazini, Hussein

    Published 2022
    “…The first modification enhances the initial population of the MBGWO using a heuristic based Ant Colony Optimisation algorithm. The second modification develops a new position update mechanism using the Bat Algorithm movement. …”
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  6. 6
    Improved Ozone Level Detection through Feature Selection with Modified Whale Optimization Algorithm

    Improved Ozone Level Detection through Feature Selection with Modified Whale Optimization Algorithm by Yab, Li Yu, Wahid, Noorhaniza, A. Hamid, Rahayu

    Published 2024
    “…The evaluation criteria include processing time, number of features selected, and classification accuracy obtained by the kNN classifier. …”
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  7. 7
    Improved Ozone Level Detection through Feature Selection with Modified Whale Optimization Algorithm

    Improved Ozone Level Detection through Feature Selection with Modified Whale Optimization Algorithm by Li Yu Yab, Li Yu Yab, Wahid, Noorhaniza, A. Hamid, Rahayu

    Published 2024
    “…The evaluation criteria include processing time, number of features selected, and classification accuracy obtained by the kNN classifier. …”
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  8. 8
    Information Theoretic-based Feature Selection for Machine Learning

    Information Theoretic-based Feature Selection for Machine Learning by Muhammad Aliyu, Sulaiman

    Published 2018
    “…The problem with many existing feature selections that evaluate features based on mutual information is that they are designed to handles classification tasks only. …”
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  9. 9
    An efficient anomaly intrusion detection method with feature selection and evolutionary neural network

    An efficient anomaly intrusion detection method with feature selection and evolutionary neural network by Sarvari, Samira, Mohd Sani, Nor Fazlida, Mohd Hanapi, Zurina, Abdullah @ Selimun, Mohd Taufik

    Published 2020
    “…This research designed an anomaly-based detection, by adopting the modified Cuckoo Search Algorithm (CSA), called Mutation Cuckoo Fuzzy (MCF) for feature selection and Evolutionary Neural Network (ENN) for classification. …”
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  10. 10
    An adaptive ant colony optimization algorithm for rule-based classification

    An adaptive ant colony optimization algorithm for rule-based classification by Al-Behadili, Hayder Naser Khraibet

    Published 2020
    “…The algorithm’s performance was compared with other variants of Ant-Miner and state-of-the-art rules-based classification algorithms based on classification accuracy and model complexity. …”
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  11. 11
    Overview of metaheuristic: classification of population and trajectory

    Overview of metaheuristic: classification of population and trajectory by Zainul Rashid, Zarina

    Published 2010
    “…The algorithm techniques can be characterized based on the criteria of the operation of the search process. …”
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  12. 12
    Improved cuckoo search based neural network learning algorithms for data classification

    Improved cuckoo search based neural network learning algorithms for data classification by Abdullah, Abdullah

    Published 2014
    “…In the proposed HACPSO algorithm, initially accelerated particle swarm optimization (APSO) algorithm searches within the search space and finds the best sub-search space, and then the CS selects the best nest by traversing the sub-search space. …”
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  13. 13
    Local Search Based Enhanced Multi-objective Genetic Algorithm of Training Backpropagation Neural Network for Breast Cancer Diagnosis

    Local Search Based Enhanced Multi-objective Genetic Algorithm of Training Backpropagation Neural Network for Breast Cancer Diagnosis by Ashraf Osman, Ibrahim, Siti Mariyam, Shamsuddin, Abdulrazak Yahya, Saleh

    Published 2017
    “…Our research is focused on enhancement of a well-known evolutionary algorithm NSGA-II by combining a local search method for solving Breast cancer classification problem based on Backpropagation neural network. …”
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  14. 14
    Ideal combination feature selection model for classification problem based on bio-inspired approach

    Ideal combination feature selection model for classification problem based on bio-inspired approach by Basir, Mohammad Aizat, Hussin, Mohamed Saifullah, Yusof, Yuhanis

    Published 2020
    “…Performance metrics are analyzed based on classification accuracy and the number of selected features. …”
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  15. 15
    Enhancing Classification Algorithms with Metaheuristic Technique

    Enhancing Classification Algorithms with Metaheuristic Technique by Cokro, Nurwinto, Tri Basuki, Kurniawan, Misinem, ., Tata, Sutabri, Yesi Novaria, Kunang

    Published 2024
    “…For this reason, in this research,several auxiliary algorithms are introduced to improve the performance of the classification algorithm, namely the meta-heuristic algorithm. …”
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  16. 16
    Content adaptive fast motion estimation based on spatio-temporal homogeneity analysis and motion classification

    Content adaptive fast motion estimation based on spatio-temporal homogeneity analysis and motion classification by Nisar, Humaira, Malik, Aamir Saeed, Choi, Tae-Sun

    Published 2012
    “…Finally, the early termination of the search process is adaptive and is based on the homogeneity between the neighboring blocks. …”
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  17. 17
    IP algorithms in compact rough classification modeling

    IP algorithms in compact rough classification modeling by Bakar, Azuraliza Abu, Sulaiman, Md Nasir, Othman, Mohamed, Selamat, Mohd Hasan

    Published 2001
    “…The paper presents the Integer Programming (IP) algorithms in mining a compact rough classification model. …”
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  18. 18
    Rule pruning techniques in the ant-miner classification algorithm and its variants: A review

    Rule pruning techniques in the ant-miner classification algorithm and its variants: A review by Al-Behadili, Hayder Naser Khraibet, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

    Published 2018
    “…Rule-based classification is considered an important task of data classification.The ant-mining rule-based classification algorithm, inspired from the ant colony optimization algorithm, shows a comparable performance and outperforms in some application domains to the existing methods in the literature.One problem that often arises in any rule-based classification is the overfitting problem. …”
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  19. 19
    Improvement on rooftop classification of worldview-3 imagery using object-based image analysis

    Improvement on rooftop classification of worldview-3 imagery using object-based image analysis by Norman, Masayu

    Published 2019
    “…Furthermore, a systematic feature selection approach was proposed in which search algorithms (Ant-Search, Best First-Search and Particle Swamp Optimization (PSO) - Search) performance were evaluated to select the most significant features. …”
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  20. 20
    Weight Optimization in Recurrent Neural Networks with Hybrid Metaheuristic Cuckoo Search Techniques for Data Classification

    Weight Optimization in Recurrent Neural Networks with Hybrid Metaheuristic Cuckoo Search Techniques for Data Classification by Nawi, N.M., Khan, A., Rehman, M.Z., Chiroma, H., Herawan, T.

    Published 2015
    “…This paper proposes a new metaheuristic search algorithm called Cuckoo Search (CS) based on Cuckoo bird’s behavior to train Elman recurrent network (ERN) and back propagation Elman recurrent network (BPERN) in achieving fast convergence rate and to avoid local minima problem. …”
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