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  1. 1
    Breast cancer disease classification using fuzzy-ID3 algorithm based on association function

    Breast cancer disease classification using fuzzy-ID3 algorithm based on association function by Nur Farahaina, Idris, Mohd Arfian, Ismail, Mohd Saberi, Mohamad, Shahreen, Kasim, Zalmiyah, Zakaria, Sutikno, Tole

    Published 2022
    “…The FID3-AF algorithm is a hybridisation of the fuzzy system, the iterative dichotomizer 3 (ID3) algorithm, and the association function. …”
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  2. 2
    A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules

    A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules by Rizauddin, Saian

    Published 2013
    “…The second proposed algorithm uses SA to optimize the terms selection while constructing a rule. …”
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  3. 3
    Functional link neural network with modified bee-firefly learning algorithm for classification task

    Functional link neural network with modified bee-firefly learning algorithm for classification task by Mohmad Hassim, Yana Mazwin

    Published 2016
    “…To overcome this, a Functional Link Neural Networks (FLNN) which has a single layer of trainable connection weights is used. …”
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  4. 4
    An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction

    An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction by Shah, Habib

    Published 2014
    “…Furthermore, here these algorithms used to train the MLP on two tasks; the seismic event's prediction and Boolean function classification. …”
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  5. 5
    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy

    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

    Published 2019
    “…However, Laplacian regularization lacks extrapolating power and biases the solution towards a constant function. These drawbacks affect the performances of Laplacian regularized semi-supervised ELMs when a few labeled data is used. …”
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  6. 6
    Jogging activity recognition using k-NN algorithm

    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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  7. 7
    Neural network training using hybrid particle-move artificial bee colony algorithm for pattern classification

    Neural network training using hybrid particle-move artificial bee colony algorithm for pattern classification by Al Nuaimi, Zakaria Noor Aldeen Mahmood, Abdullah, Rosni

    Published 2017
    “…However, hybrid algorithms are also a fundamental concern in the optimization field, which aim to cumulate the advantages of different algorithms into one algorithm. …”
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  8. 8
    An approach to improve functional link neural network training using modified artificial bee colony for classification task

    An approach to improve functional link neural network training using modified artificial bee colony for classification task by Mohmad Hassim, Yana Mazwin, Ghazali, Rozaida

    Published 2012
    “…The standard method for tuning the weight in FLNN is using a Backpropagation (BP) learning algorithm. …”
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  9. 9
    An approach to improve functional link neural network training using modified artificial bee colony for classification task

    An approach to improve functional link neural network training using modified artificial bee colony for classification task by Mohmad Hassim, Yana Mazwin, Ghazali, Rozaida

    Published 2012
    “…The standard method for tuning the weight in FLNN is using a Backpropagation (BP) learning algorithm. …”
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  10. 10
    Fair bandwidth distribution marking and scheduling algorithm in network traffic classification

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

    Published 2019
    “…Therefore, in order to improve bandwidth fairness along with efficient optimization to alleviate this problem, we propose two marker algorithms; a Double Modified Double Improved time sliding window Three Colour Marker (M2I2TSWTCM) algorithm, which makes a new value of that depends on the logarithm peak information rate (PIR) and which is added to the adaptive factor that exists in the previous algorithm. …”
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  11. 11
    Neural Network Training Using Hybrid Particle-move Artificial Bee Colony Algorithm for Pattern Classification

    Neural Network Training Using Hybrid Particle-move Artificial Bee Colony Algorithm for Pattern Classification by Nuaimi, Zakaria Noor Aldeen Mahmood Al, Abdullah, Rosni

    Published 2017
    “…However, hybrid algorithms are also a fundamental concern in the optimization field, which aim to cumulate the advantages of different algorithms into one algorithm. …”
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  12. 12
    An approach to improve functional link neural network training using modified artificial bee colony for classification task

    An approach to improve functional link neural network training using modified artificial bee colony for classification task by Yana Mazwin Mohmad Hassim, Rozaida Ghazali

    Published 2013
    “…The standard method for tuning the weight in FLNN is using a Backpropagation (BP) learning algorithm. …”
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  13. 13
    An Improved Wavelet Neural Network For Classification And Function Approximation

    An Improved Wavelet Neural Network For Classification And Function Approximation by Ong , Pauline

    Published 2011
    “…First, the types of activation functions used in the hidden layer of the WNN were varied. …”
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  14. 14
    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model

    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
    “…EM and K-means clustering algorithms are used to cluster the multi-class classification attribute according to its relevance criteria and afterward, the clustered attributes are classified using an ensemble random forest classifier model. …”
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  15. 15
    Support directional shifting vector: A direction based machine learning classifier

    Support directional shifting vector: A direction based machine learning classifier by Kowsher, Md., Hossen, Imran, Tahabilder, Anik, Prottasha, Nusrat Jahan, Habib, Kaiser, Zafril Rizal, M Azmi

    Published 2021
    “…The positional error of the linear function has been modelled as a loss function which is iteratively optimized using the gradient descent algorithm. …”
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  16. 16
    Mutable Composite Firefly Algorithm for Microarray-Based Cancer Classification

    Mutable Composite Firefly Algorithm for Microarray-Based Cancer Classification by Fajila, Fathima, Yusof, Yuhanis

    Published 2024
    “…In addition, the local optima issue is overcome by the population reinitialisation method. The proposed algorithm, named the CFS-Mutable Composite Firefly Algorithm (CFS-MCFA), is evaluated based on two metrics, namely classification accuracy and genes subset size, using a Support Vector Machine (SVM) classifier. …”
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  17. 17
    Improving amphetamine-type stimulants drug classification using chaotic-based time-varying binary whale optimization algorithm

    Improving amphetamine-type stimulants drug classification using chaotic-based time-varying binary whale optimization algorithm by Draman @ Muda, Azah Kamilah, Mohd Yusof, Norfadzlia, Pratama, Satrya Fajri, Carbo-Dorca, Ramon, Abraham, Ajith

    Published 2022
    “…Firstly, a non-linear time-varying modified Sigmoid transfer function is used as the binarization method. …”
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  18. 18
    A new mobile botnet classification based on permission and API calls

    A new mobile botnet classification based on permission and API calls by Yusof M., Madihah Mohd Saudi, Farida Hazwani Mohd Ridzuan

    Published 2024
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  19. 19
    A novel nonlinear time‑varying sigmoid transfer function in binary whale optimization algorithm for descriptors selection in drug classifcation

    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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  20. 20
    A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani

    A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani by Mahmoud Reza, Saybani

    Published 2016
    “…The FSR-AIRS2 is a new hybrid algorithm that incorporates the FRA, RRC, and the SVM into AIRS2 in order to produce a stronger classifier. …”
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