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  1. 1
    Deep learning-based colorectal cancer classification using augmented and normalised gut microbiome data / Mwenge Mulenga

    Deep learning-based colorectal cancer classification using augmented and normalised gut microbiome data / Mwenge Mulenga by Mwenge , Mulenga

    Published 2022
    “…Therefore, to address the above-mentioned limitations in deep learning classification of colorectal cancer based on gut microbiome data, three objectives were formulated. …”
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  2. 2
    Poverty risk prediction based on socioeconomic factors using machine learning approach

    Poverty risk prediction based on socioeconomic factors using machine learning approach by Mohd Zawari, Nur Farhana Adibah

    Published 2025
    “…This study seeks to develop a predictive model of measuring poverty risk using socioeconomic factors based on a machine learning framework. …”
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  3. 3
    New Instances Classification Framework On Quran Ontology Applied To Question Answering System

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

    Published 2019
    “…The existing classification approach used machine learning: Backpropagation Neural Network. …”
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  4. 4
    Hybrid data regression model based on the generalized adaptive resonance theory neural network

    Hybrid data regression model based on the generalized adaptive resonance theory neural network by Wong S.Y., Yap K.S., Lim C.P., Lee E.W.M.

    Published 2023
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  5. 5
    Combining cluster quality index and supervised learning to predict students’ academic performance

    Combining cluster quality index and supervised learning to predict students’ academic performance by Suhaila Zainudin, Rapi’ah Ibrahim, Hafiz Mohd Sarim

    Published 2024
    “…The best cluster is further analysed using classification to predict students’ academic performance. …”
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  6. 6
    On equivalence of FIS and ELM for interpretable rule-based knowledge representation

    On equivalence of FIS and ELM for interpretable rule-based knowledge representation by Wong S.Y., Yap K.S., Yap H.J., Tan S.C., Chang S.W.

    Published 2023
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  7. 7
    Developing framework for natphoric computer-aided web-based kansei engineering / Mohammad Bakri Che Haron

    Developing framework for natphoric computer-aided web-based kansei engineering / Mohammad Bakri Che Haron by Che Haron, Mohammad Bakri

    Published 2013
    “…The Natphoric algorithm learns the process done by training with sets of training data from previous KE research works. …”
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  8. 8
    Ensemble learning using multi-objective optimisation for arabic handwritten words

    Ensemble learning using multi-objective optimisation for arabic handwritten words by Ghadhban, Haitham Qutaiba

    Published 2021
    “…Most ensemble learning approaches are based on the assumption of linear combination, which is not valid due to differences in data types. …”
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  9. 9
    Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines

    Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines by Aker, Elhadi Emhemed Alhaaj Ammar

    Published 2020
    “…This current study proposes an intelligent data mining approach for the Machine Learning- Adaptive Distance Relay (ML-ADR) fault classification model using novel extracted 1-cycle transient voltage and current signals hidden knowledge from both healthy and faulty lines parameters. …”
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  10. 10
    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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  11. 11
    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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  12. 12
    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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  13. 13
    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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  14. 14
    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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  15. 15
    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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  16. 16
    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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  17. 17
    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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  18. 18
    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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  19. 19
    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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  20. 20
    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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