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  1. 1

    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…Expectation maximization (EM) is one of the representatives clustering algorithms which have broadly applied in solving classification problems by improving the density of data using the probability density function. …”
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    Article
  2. 2

    A novel nonlinear time‑varying sigmoid transfer function in binary whale optimization algorithm for descriptors selection in drug classifcation by Mohd Yusof, Norfadzlia, Muda, Azah Kamilah, Pratama, Satrya Fajri, Abraham, Ajith

    Published 2022
    “…The comparative optimization algorithms include two BWOA variants, binary bat algorithm (BBA), binary gray wolf algorithm (BGWOA), and binary manta-ray foraging algorithm (BMRFO). …”
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  3. 3

    Realization of Generalized RBF Network by Lee, Nung Kion, Wang, Dianhui

    Published 2003
    “…Neural classifiers have been widely used in many application areas. This paper describes generalized neural classifier based on the radial basis function network. …”
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    Proceeding
  4. 4

    Jogging activity recognition using k-NN algorithm by Afifah Ismail

    Published 2022
    “…The k-NN algorithm is a simple and easy-to-implement supervised machine learning algorithm that can be used to solve both classification and regression problems. …”
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    Academic Exercise
  5. 5

    Fair bandwidth distribution marking and scheduling algorithm in network traffic classification by Al-Kharasani, Ameen Mohammed Abdulkarem

    Published 2019
    “…Second, propose an Optimized Time Sliding Window based Three Colour Marker. Finally, propose a new method of obtaining optimal parameters dropping functions for Random Early Detection (RED) algorithm. …”
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    Thesis
  6. 6

    New Learning Models for Generating Classification Rules Based on Rough Set Approach by Al Shalabi, Luai Abdel Lateef

    Published 2000
    “…Classification rules were generated based on the best reduct. For the problem of missing data, a new approach was proposed based on data partitioning and function mode. …”
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    Thesis
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  8. 8

    Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm by Dalatu, Paul Inuwa

    Published 2018
    “…The problem of using range function in Heterogeneous Euclidean-Overlap Metric (HEOM) is addressed by replacing the range with interquartile range function called Interquartile Range-Heterogeneous Metric (IQR-HEOM). …”
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    Thesis
  9. 9
  10. 10

    A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

    Published 2016
    “…The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
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    Thesis
  11. 11

    New Instances Classification Framework On Quran Ontology Applied To Question Answering System by Utomo, Fandy Setyo, Suryana, Nanna, Azmi, Mohd Sanusi

    Published 2019
    “…As a result, the instances classification framework consists of several essential components: pre-processing, morphology analysis, semantic analysis, feature extraction, instances classification with Radial Basis Function Networks algorithm, and the transformation module. …”
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    Article
  12. 12

    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

    Published 2018
    “…Therefore, this research has designed fuzzy learning algorithm that is able to classify fruits based on their shape and size features using Harumanis dataset. …”
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    Thesis
  13. 13

    Short Text Classification Using An Enhanced Term Weighting Scheme And Filter-Wrapper Feature Selection by Alsmadi, Issa Mohammad Ibrahim

    Published 2018
    “…Redundancy and noise in short texts are common problems in social media and in different applications that use short text. …”
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    Thesis
  14. 14
  15. 15

    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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    Article
  16. 16

    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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    Article
  17. 17

    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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    Article
  18. 18

    Classification of polymorphic virus based on integrated features by A Hamid, Isredza Rahmi, Subramaniam, Sharmila, Sutoyo, Edi, Abdullah, Zubaile

    Published 2018
    “…Standard virus classification relies on the use of virus function, which is a small number of bytes written in assembly language. …”
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    Article
  19. 19

    RMIL/AG: A new class of nonlinear conjugate gradient for training back propagation algorithm by Basri, S.M.M., Nawi, N.M., Mamat, M., Hamid, N.A.

    Published 2018
    “…This paper introduced a new class of efficient second order conjugate gradient (CG) for training BP called Rivaie, Mustafa, Ismail and Leong (RMIL)/AG. The RMIL uses the value of adaptive gain parameter in the activation function to modify the gradient based search direction. …”
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    Conference or Workshop Item
  20. 20

    Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection by Too, Jing Wei, Abdullah, Abdul Rahim

    Published 2020
    “…The proposed methods show superior results in several benchmark function tests. As for EMG feature selection, the proposed algorithms are evaluated using the EMG data acquired from the publicly access EMG database. …”
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    Article