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  1. 1
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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  2. 2
    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…The support vector machines (SVM) algorithm obtained the overall best results of 94.5% accuracy, 91.8% precision, 91.7% recall, and 91.1% f-Measure while the naïve bayes (NB) algorithm obtained the best AUC score of 0.944 with the tweet data of Dato Seri Anwar. …”
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  3. 3
    Algorithm-program visualization model : An intergrated software visualzation to support novices' programming comprehension

    Algorithm-program visualization model : An intergrated software visualzation to support novices' programming comprehension by Affandy

    Published 2015
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  4. 4
    Hand gesture recognition for autism diagnosis using Support Vector Machine (SVM) Algorithm / Muhammad Asyraf Mohamad Zain

    Hand gesture recognition for autism diagnosis using Support Vector Machine (SVM) Algorithm / Muhammad Asyraf Mohamad Zain by Mohamad Zain, Muhammad Asyraf

    Published 2020
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  5. 5
    Evaluation of data mining classification and clustering techniques for diabetes / Tuba Pala and Ali Yilmaz Camurcu

    Evaluation of data mining classification and clustering techniques for diabetes / Tuba Pala and Ali Yilmaz Camurcu by Pala, Tuba, Camurcu, Ali Yilmaz

    Published 2014
    “…Multilayer Perceptron algorithm has been the best algorithm with the highest success percentage in both of the programs; Decision Trees has been the algorithm which has the lowest success percentage again in both of the programs. …”
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  6. 6
    Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed co-gasification of biomass wastes from oil palm

    Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed... by Ayodele B.V., Mustapa S.I., Kanthasamy R., Mohammad N., AlTurki A., Babu T.S.

    Published 2023
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  7. 7
    Virtual reality in algorithm programming course: practicality and implications for college students

    Virtual reality in algorithm programming course: practicality and implications for college students by Dewi, Ika Parma, Ambiyar, Mursyida, Lativa, Effendi, Hansi, Giatman, Muhammad, Efrizon, Hanafi, Hafizul Fahri, Ali, Siti Khadijah

    Published 2024
    “…The reliability of VR supports various variations in learning, including learning programming algorithms. …”
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  8. 8
    Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed co-gasification of biomass wastes from oil palm

    Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed... by Ayodele, B.V., Mustapa, S.I., Kanthasamy, R., Mohammad, N., AlTurki, A., Babu, T.S.

    Published 2022
    “…Taking advantage of the data generated from the process, this study explores the performance of twelve machine learning algorithms built on the support vector machine (SVM), the Gaussian process regression (GPR), and the non-linear response quadratic model (NLRQM) using Sequential quadratic programming, and the Levenberg-Marquardt algorithms. …”
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  9. 9
    Different mutation and crossover set of genetic programming in an automated machine learning

    Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

    Published 2020
    “…This paper presents the effect of different pairs of mutation and crossover rates on the automated machine learning performances that tested on different types of datasets. The finding can be used to support the theory that higher crossover rates used to improve the algorithm accuracy score while lower crossover rates may cause the algorithm to converge at earlier stage. …”
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  10. 10
    Different mutation and crossover set of genetic programming in an automated machine learning

    Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

    Published 2020
    “…This paper presents the effect of different pairs of mutation and crossover rates on the automated machine learning performances that tested on different types of datasets. The finding can be used to support the theory that higher crossover rates used to improve the algorithm accuracy score while lower crossover rates may cause the algorithm to converge at earlier stage. …”
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  11. 11
    Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed co-gasification of biomass wastes from oil palm

    Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed... by Ayodele, B.V., Mustapa, S.I., Kanthasamy, R., Mohammad, N., AlTurki, A., Babu, T.S.

    Published 2022
    “…Taking advantage of the data generated from the process, this study explores the performance of twelve machine learning algorithms built on the support vector machine (SVM), the Gaussian process regression (GPR), and the non-linear response quadratic model (NLRQM) using Sequential quadratic programming, and the Levenberg-Marquardt algorithms. …”
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  12. 12
    Predicting uniaxial compressive strength using Support Vector Machine algorithm

    Predicting uniaxial compressive strength using Support Vector Machine algorithm by Zakaria, Hafedz, Abdullah, Rini Asnida, Ismail, Amelia Ritahani, Amin, Mohd For

    Published 2019
    “…An algorithm has been tested on a series of rock data using dry density and velocity parameters. …”
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  13. 13
    Early autism spectrum disorder detection using machine learning / Muhammad Shahmi Shahron Nizan

    Early autism spectrum disorder detection using machine learning / Muhammad Shahmi Shahron Nizan by Shahron Nizan, Muhammad Shahmi

    Published 2023
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  14. 14
    Comparison of algorithm Support Vector Machine and C4.5 for identification of pests and diseases in chili plants

    Comparison of algorithm Support Vector Machine and C4.5 for identification of pests and diseases in chili plants by M, Irfan, N, Lukman, A. A, Alfauzi, J, Jumadi

    Published 2019
    “…The use of data mining algorithms is expected to help in the identification of pests and diseases in chili plants. …”
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    Conference or Workshop Item
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  15. 15
    An optimal mesh algorithm for remote protein homology detection

    An optimal mesh algorithm for remote protein homology detection by M. Abdullah, Firdaus, M. Othman, Razib, Kasim, Shahreen, Hashim, Rathiah, Hassan, Rohayanti, Asmuni, Hishammuddin, Taliba, Jumail

    Published 2011
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  16. 16
    Building extraction of worldview3 imagery via support vector machine using scikit-learn module / Najihah Ismail

    Building extraction of worldview3 imagery via support vector machine using scikit-learn module / Najihah Ismail by Ismail, Najihah

    Published 2021
    “…Moreover, the capability of the programming based using python for building extraction can be assessed. …”
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  17. 17
    Face recognition using eigenfaces and smooth support vector machine

    Face recognition using eigenfaces and smooth support vector machine by Mhd, Furqan

    Published 2011
    “…Smoothing methods, extensively used for solving important mathematical programming problems and applications. …”
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  18. 18
    Face recognition using eigenfaces and smooth support vector machine

    Face recognition using eigenfaces and smooth support vector machine by Mhd, Furqan

    Published 2011
    “…Smoothing methods, extensively used for solving important mathematical programming problems and applications. …”
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    Undergraduates Project Papers
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  19. 19
    Satisfiable Integer Programming Algorithm On Distributed Inter Process Communication (SIP-DIPC)

    Satisfiable Integer Programming Algorithm On Distributed Inter Process Communication (SIP-DIPC) by Abdul Hamid, Mohd Hakim, Abu, Nur Azman, Mohamad, Siti Nurul Mahfuzah, Idris, Aris, Zakaria, Zahriladha, Sulaiman, Zuraidah

    Published 2019
    “…Satisfiable Integer Programming (SIP) has been used to quantify dataset in Rough Classification Modeling (RCM). …”
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  20. 20
    WURFL detection engine using cosine string similarity algortlhm / Illiasaak Ahmad ... [et al.]

    WURFL detection engine using cosine string similarity algortlhm / Illiasaak Ahmad ... [et al.] by Ahmad, Illiasaak, Anak Buja, Alya@Geogiana, Abdullah Sani, Anis Shobirin

    Published 2013
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