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  1. 1
    Lexicon-based and immune system based learning methods in Twitter sentiment analysis

    Lexicon-based and immune system based learning methods in Twitter sentiment analysis by Jantan, Hamidah, Drahman, Fatimatul Zahrah, Alhadi, Nazirah, Mamat, Fatimah

    Published 2016
    “…The aim of this article attempts to study the potential of this method in text classification for sentiment analysis.This study consists of three phases; data preparation; classification model development using three selected Immune System based algorithms i.e. …”
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  2. 2
    Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves

    Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves by Lia, Kamelia

    Published 2024
    “…The proposed method integrates colour and texture feature-based image analysis with machine learning algorithms for classification. …”
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  3. 3
    New learning algorithm based on Hidden Markov Model (HMM) as stochastic modelling for pattern calssification

    New learning algorithm based on Hidden Markov Model (HMM) as stochastic modelling for pattern calssification by Balakrishnan, Malarvili, Ting, Chee Ming, Shaikh Salleh, Sheikh Hussain

    Published 2009
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  4. 4
    Class binarization with self-adaptive algorithm to improve human activity recognition

    Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…However, the learning complexity of classification is increased due to the expansion number of learning model. …”
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  5. 5
    Case Slicing Technique for Feature Selection

    Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

    Published 2004
    “…One of the problems addressed by machine learning is data classification. Finding a good classification algorithm is an important component of many data mining projects. …”
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  6. 6
    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition

    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

    Published 2017
    “…Whereas for supervised learning method, it requires teacher or prior data (i.e. large, prohibitive and labelled training data) during classification process which in real life, the cost of obtaining sufficient labelled training data is high. …”
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  7. 7
    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
    “…In data mining, classification learning is broadly categorized into two categories; supervised and unsupervised. …”
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  8. 8
    VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern

    VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern by Angeline Teoh, Szu Fern

    Published 2012
    “…These two models are based on topological placement method. DM is optimized using genetic algorithm (GA). …”
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  9. 9
    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
    “…Feature selection and classification are widely utilized for data analysis. …”
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  10. 10
    Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach

    Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach by Moheb Pour, Majid Reza

    Published 2009
    “…The two algorithms were compared, and the proposed algorithm was found to be able to both learn and classify quickly. …”
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  11. 11
    New Learning Models for Generating Classification Rules Based on Rough Set Approach

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

    Published 2000
    “…Two different models for learning in data sets were proposed based on two different reduction algorithms. …”
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  12. 12
    Performances of machine learning algorithms for binary classification of network anomaly detection system

    Performances of machine learning algorithms for binary classification of network anomaly detection system by Nawir, M., Amir, A., Lynn, O.B., Yaakob, N., Ahmad, R.B.

    Published 2018
    “…Moreover, network anomaly detection using machine learning faced difficulty when dealing the involvement of dataset where the number of labelled network dataset is very few in public and this caused many researchers keep used the most commonly network dataset (KDDCup99) which is not relevant to employ the machine learning (ML) algorithms for a classification. …”
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  13. 13
    Comparative study of machine learning algorithms in data classification

    Comparative study of machine learning algorithms in data classification by Tan, Kai Jun

    Published 2025
    “…This research conducts a comparative study of various machine learning algorithms for dataset classification to identify the most accurate and reliable classifier. …”
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  14. 14
    Evaluation of the Transfer Learning Models in Wafer Defects Classification

    Evaluation of the Transfer Learning Models in Wafer Defects Classification by Jessnor Arif, Mat Jizat, Anwar, P. P. Abdul Majeed, Ahmad Fakhri, Ab. Nasir, Zahari, Taha, Yuen, Edmund, Lim, Shi Xuen

    Published 2022
    “…Transfer Learning is one of the common methods. Various algorithms under Transfer Learning had been developed for different applications. …”
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  15. 15
    Multi-Class Multi-Level Classification of Mental Health Disorders Based on Textual Data from Social Media

    Multi-Class Multi-Level Classification of Mental Health Disorders Based on Textual Data from Social Media by Sutranggono, Abi Nizar, Sarno, Riyanarto, Ghozali, Imam

    Published 2024
    “…The Multi-Class Multi-Level (MCML) classification algorithm was applied to perform detailed classification and address the limitations of the research scope using several approaches, including machine learning, deep learning, and transfer learning approaches. …”
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  16. 16
    An improved algorithm for iris classification by using support vector machine and binary random machine learning

    An improved algorithm for iris classification by using support vector machine and binary random machine learning by Kamarulzalis, Ahmad Haadzal

    Published 2018
    “…In machine learning, there are three type of learning branch that can used in classification procedures for data mining. …”
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  17. 17
    Tree-based contrast subspace mining method

    Tree-based contrast subspace mining method by Florence Sia Fui Sze

    Published 2020
    “…Hence, this thesis presents the optimization of parameters values for the tree-based method by genetic algorithm. …”
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  18. 18
    Training functional link neural network with ant lion optimizer

    Training functional link neural network with ant lion optimizer by Mohmad Hassim, Yana Mazwin, Ghazali, Rozaida

    Published 2020
    “…This paper proposed the implementation of Ant Lion Algorithm as learning algorithm to train the FLNN for classification tasks. …”
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  19. 19
    Minimizing Classification Errors in Imbalanced Dataset Using Means of Sampling

    Minimizing Classification Errors in Imbalanced Dataset Using Means of Sampling by Khan I., Ahmad A.R., Jabeur N., Mahdi M.N.

    Published 2023
    “…Classification (of information); Learning algorithms; Students; Class imbalance; Data level; Over sampling; Performance prediction; SMOTE; Spread subsampling; Student performance; Student performance prediction; Under-sampling; Machine learning…”
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  20. 20
    Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif

    Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif by Jantan, Hamidah, Mat Yusof, Norazmah, Abdul Latif, Mohd Hanapi

    Published 2014
    “…Support Vector Machine (SVM) is among the popular learning algorithm for classification in soft computing techniques. …”
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