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  1. 1
    Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms

    Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms by Rachmad, Iqbal, Tri Basuki, Kurniawan, Misinem, ., Edi Surya, Negara, Tata, Sutabri

    Published 2024
    “…This research proposes a low-cost alternative using intelligent fruit selection systems based on computer vision techniques to address these issues. …”
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  2. 2
    Predicting 30-day mortality after an acute coronary syndrome (ACS) using machine learning methods for feature selection, classification and visualization

    Predicting 30-day mortality after an acute coronary syndrome (ACS) using machine learning methods for feature selection, classification and visualization by Nanyonga Aziida, Sorayya Malek, Firdaus Aziz, Khairul Shafiq Ibrahim, Sazzli Kasim

    Published 2021
    “…Identifying a feature selection method with a classifier algorithm that produces high performance in mortality studies is essential and has not been reported before. …”
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  3. 3
    Enhancing understanding of programming concepts through physical games

    Enhancing understanding of programming concepts through physical games by Raja Yusof, Raja Jamilah, Habib, Ahsan

    Published 2017
    “…We produced in total 10 lesson games to illustrate variables, swapping, arrays, sorting algorithm particularly bubble sort, quicksort, selection sort, graph theory, dynamic programming, amortized analysis and trees. …”
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  4. 4
    Chemometrics analysis for the detection of dental caries via ultraviolet absorption spectroscopy / Katrul Nadia Basri

    Chemometrics analysis for the detection of dental caries via ultraviolet absorption spectroscopy / Katrul Nadia Basri by Basri, Katrul Nadia

    Published 2023
    “…Dimension reduction algorithm such as LDA and CNN were applied on the spectra to reduce the number of variables to be trained. …”
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  5. 5
    High-Resolution Downscaling with Interpretable Relevant Vector Machine: Rainfall Prediction for Case Study in Selangor

    High-Resolution Downscaling with Interpretable Relevant Vector Machine: Rainfall Prediction for Case Study in Selangor by Abdul Rashid, Raghdah Rasyidah, Shaharudin, Shazlyn Milleana, Sulaiman, Nurul Ainina Filza, Zainuddin, Nurul Hila, Mahdin, Hairulnizam, Mohd Najib, Summayah Aimi, Hidayat, Rahmat

    Published 2024
    “…The Principal Component Analysis (PCA) technique was employed to choose relevant environmental variables as input for the machine learning model, and various imputation methods were utilized to manage missing data, such as mean imputation and the KNN algorithm. …”
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  6. 6
    Bayesian network of influence of sociodemographic variables on dengue related knowledge, attitude, and practices in selected areas in Selangor, Malaysia

    Bayesian network of influence of sociodemographic variables on dengue related knowledge, attitude, and practices in selected areas in Selangor, Malaysia by Ajibola, Lamidi-Sarumoh Alaba

    Published 2019
    “…The data collected was used to learn the structure of BN via some known algorithms using R programming language. …”
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  7. 7
    Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique

    Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique by Hardev Singh, Jitvinder Dev Singh

    Published 2015
    “…The variable block matching developed based on four stages which is the video and frame selection, threshold calculation, block size selection and search pattern. …”
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  8. 8
    Taguchi?s T-method with Normalization-Based Binary Bat Algorithm

    Taguchi?s T-method with Normalization-Based Binary Bat Algorithm by Marlan Z.M., Jamaludin K.R., Harudin N.

    Published 2025
    “…Therefore, a variable selection technique using a swarm-based Binary Bat algorithm is proposed. …”
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  9. 9
    A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models

    A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

    Published 2017
    “…The focus of the paper is to propose a hybrid approach for the selection of the most influential input variables for the training and testing of neural network based hybrid models. …”
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  10. 10
    Robust variable selection methods for large- scale data in the presence of multicollinearity, autocorrelated errors and outliers

    Robust variable selection methods for large- scale data in the presence of multicollinearity, autocorrelated errors and outliers by Uraibi, Hassan S.

    Published 2016
    “…We develop Robust Forward Selection algorithm based on RFCH correlation coefficient (RFS.RFCH) because FS.Winso is not robust to multivariate outliers. …”
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  11. 11
    Dynamic Bayesian Networks and Variable Length Genetic Algorithm for Dialogue Act Recognition

    Dynamic Bayesian Networks and Variable Length Genetic Algorithm for Dialogue Act Recognition by Ali Yahya, Anwar

    Published 2007
    “…In the selection phase, a new variable length genetic algorithm is applied to select the lexical cues. …”
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  12. 12
    The Development Of System For Algorithms Visualization Using Simjava

    The Development Of System For Algorithms Visualization Using Simjava by Jamil Alsayaydeh, Jamil Abedalrahim, Ahmad Idil, Abdul Rahman, Zainon, Maslan, Aziz, Azwan, Zikri Abadi, Baharudin, Oliinyk, Andrii

    Published 2020
    “…It does not simply fit data to a chart to visualize an algorithm, there is no main data set. …”
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  13. 13
    Mixed-variable ant colony optimisation algorithm for feature subset selection and tuning support vector machine parameter

    Mixed-variable ant colony optimisation algorithm for feature subset selection and tuning support vector machine parameter by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2017
    “…ACOMV-SVM algorithm is able to simultaneously tune SVM parameters and feature subset selection. …”
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  14. 14
    Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition

    Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition by Yahya, Anwar Ali, Mahmod, Ramlan, Ramli, Abd Rahman

    Published 2010
    “…In the second stage, the developed variable length genetic algorithm is used to select different sets of lexical cues to constitute the dynamic Bayesian networks' random variables. …”
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  15. 15
    Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data

    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

    Published 2023
    “…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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  16. 16
    Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data

    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

    Published 2023
    “…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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  17. 17
    Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data

    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

    Published 2023
    “…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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  18. 18
    Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification

    Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification by Abd Samad, Md Fahmi

    Published 2011
    “…A deterministic mutation-based algorithm is introduced to overcome this problem. …”
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  19. 19
    Budget visualizer using circle packing technique / Nursyahira Zulkeply

    Budget visualizer using circle packing technique / Nursyahira Zulkeply by Zulkeply, Nursyahira

    Published 2019
    “…In order to construct this data visualization, the circle packing algorithm is used to visualize these budgets. …”
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  20. 20
    Formulating new enhanced pattern classification algorithms based on ACO-SVM

    Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
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