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

“…The second modification develops a new position update mechanism using the Bat Algorithm movement. The third modification improves the controlled parameter of the MBGWO algorithm using indicators from the search process to refine the solution. …”
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Metaheuristic algorithms for feature selection (2014–2024) by Faizan, Muhammad, Muhammad Arif, Mohamad

“…Metaheuristic algorithms are suited to provide solutions to feature selection problems because these problems are combinatorial and require an effective and efficient search through large solution spaces. …”
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Enhancement of Ant System Algorithm for Course Timetabling Problem by Djamarus, Djasli

“…Results of the experiments that were conducted using various data sets showed that the proposed algorithm produced better course schedule solution than the Greedy Algorithm, Genetic Algorithm, and other variants of Ant System Algorithm.…”
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Utilizing artificial bee colony algorithm as feature selection method in Arabic text classification by Hijazi, Musab, Zeki, Akram M., Ismail, Amelia Ritahani

“…One of the widely used algorithms for feature selection in text classification is the Evolutionary algorithm . …”
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EEG-and MRI-based epilepsy source localization using multivariate empirical mode decomposition and inverse solution method by Khosropanah, Pegah

“…Standardized Low Resolution Tomography (sLORETA) andWeighted Minimum Norm (WMN) are linear distributed inverse solutions which lead up to zero localization error using noise-free EEG, state-of-the-art feature extractor and realistic head model. …”
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A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification by Talpur, N., Abdulkadir, S.J., Hasan, M.H., Alhussian, H., Alwadain, A.

“…Moreover, K-Nearest Neighbor (KNN) classifier was used to evaluate the effectiveness of the features identified by the proposed SCSO algorithm. …”
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Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data by Qadir Saraf, Tara Othman, Fuad, Norfaiza, Md Taujuddin, Nik Shahidah Afifi

“…Meta-heuristic searching with embedding information theory-based criteria in the fitness function for selecting the relevant features is used widely in current feature selection algorithms. …”
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Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data by Qadir Saraf, Tara Othman, Fuad, Norfaiza, Md Taujuddin, Nik Shahidah Afifi

“…Meta-heuristic searching with embedding information theory-based criteria in the fitness function for selecting the relevant features is used widely in current feature selection algorithms. …”
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Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data by Qadir Sara, Tara Othman, Fuad, Norfaiza, Md Taujuddin, Nik Shahidah Afifi

“…Meta-heuristic searching with embedding information theory-based criteria in the fitness function for selecting the relevant features is used widely in current feature selection algorithms. …”
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Mutable Composite Firefly Algorithm for Microarray-Based Cancer Classification by Fajila, Fathima, Yusof, Yuhanis

“…Thus, a swarm-based hybrid approach is proposed for cancer classification with a new variant of the Firefly Algorithm (FA) and Correlation-based Feature Selection (CFS) filter. …”
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Improved whale optimization algorithm for feature selection in Arabic sentiment analysis by Tubishat, Mohammad, Abushariah, Mohammad A.M., Idris, Norisma, Aljarah, Ibrahim

“…The comprehensive experiments results show that the proposed algorithm outperforms all other algorithms in terms of sentiment analysis classification accuracy through finding the best solutions, while its also minimizes the number of selected features. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.…”
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Intelligent classification algorithms in enhancing the performance of support vector machine by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…The algorithms are called ACOMVSVM and IACOMV-SVM. The difference between the algorithms is the size of the solution archive. …”
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Enhancing Classification Algorithms with Metaheuristic Technique by Cokro, Nurwinto, Tri Basuki, Kurniawan, Misinem, ., Tata, Sutabri, Yesi Novaria, Kunang

“…Meta-heuristic algorithms are search techniques used to solve complexoptimization problems, and these algorithms can help provide reasonable solutions in a shorter time thanexact methods. …”
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Optimized Cover Selection for Audio Steganography Using Multi-Objective Evolutionary Algorithm by Noor Azam, Muhammad Harith, Ridzuan, Farida, Mohd Sayuti, M Norazizi Sham

“…As a trade-off exists between capacity and imperceptibility, producing a method focused on optimising both features is crucial. One of the search methods commonly used to find solutions for the trade-off problem in various fields is the Multi-Objective Evolutionary Algorithm (MOEA). …”
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

“…In addition, it is considered that existing solutions do not provide a feature driftaware solution to the concept drift adaptable solution, which exploits the fact that many of the original features are non-relevant. …”
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

“…The proposed algorithm is compared with the state-of-the-art feature selection algorithms using three different datasets. …”
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Enhancement of feature sets for subjectivity analysis on Malay-English code-switching text by Kasmuri, Emaliana

“…In the unified code-switching feature set, the extracted Malay and English features were unified using an adapted algorithm known as the Malay-English Unified POS. …”
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Bat Algorithm Based Hybrid Filter-Wrapper Approach by Taha A.M., Chen S.-D., Mustapha A.

“…In BAMI, MI was used to identify promising features which could potentially accelerate the process of finding the best known solution. …”

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

“…The proposed search algorithm uses mutation to more accurately examine the search space, to allow candidates to escape local minima. …”
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Arabic Text Clustering Methods And Suggested Solutions For Theme-based Quran Clustering: Analysis Of Literature by Qusay Bsoul, Jaffar Atwan, Rosalina Abdul Salam, Malik Jawarneh