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  1. 1
    Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering

    Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering by He, Yanfang

    Published 2024
    “…Although the swmcan algorithm solves the noise problem in multi-view data, its initial and final graphs are independent and cannot learn from each other. …”
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  2. 2
    An Improved Pheromone-Based Kohonen Self- Organising Map in Clustering and Visualising Balanced and Imbalanced Datasets

    An Improved Pheromone-Based Kohonen Self- Organising Map in Clustering and Visualising Balanced and Imbalanced Datasets by Ahmad, Azlin, Yusof, Rubiyah, Zulkifli, Nor Saradatul Akma, Ismail, Mohd Najib

    Published 2021
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  3. 3
    A Survey Of Supervised Machine Learning In Wireless Sensor Network: A Power Management Perspective

    A Survey Of Supervised Machine Learning In Wireless Sensor Network: A Power Management Perspective by Ul haq, Riaz, Norrozila, Sulaiman, Muhammad, Alam

    Published 2013
    “…Machine learning algorithms are iteration based algorithms, as the new knowledge is based on the previous predicted /calculated knowledge which helps to decrease errors in order to increase efficiency. …”
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  4. 4
    Improved Parameterless K-Means: Auto-Generation Centroids and Distance Data Point Clusters

    Improved Parameterless K-Means: Auto-Generation Centroids and Distance Data Point Clusters by Wan Maseri, Wan Mohd, Beg, Abul Hashem, Herawan, Tutut, Noraziah, Ahmad

    Published 2011
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  5. 5
    A cluster analysis of population based cancer registry in Brunei Darussalam : an exploratory study

    A cluster analysis of population based cancer registry in Brunei Darussalam : an exploratory study by Lai, Daphne Teck Ching, Owais A. Malik

    Published 2022
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  6. 6
    Hyper-heuristic framework for sequential semi-supervised classification based on core clustering

    Hyper-heuristic framework for sequential semi-supervised classification based on core clustering by Adnan, Ahmed, Muhammed, Abdullah, Abd Ghani, Abdul Azim, Abdullah, Azizol, Huyop @ Ayop, Fahrul Hakim

    Published 2020
    “…This article presents a prominent framework that integrates each of the NN, a meta-heuristic based on evolutionary genetic algorithm (GA) and a core online-offline clustering (Core). …”
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  7. 7
    Support Vector Machines (SVM) in Test Extraction

    Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

    Published 2006
    “…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. …”
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    Final Year Project
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  8. 8
    Support Vector Machines (SVM) in Test Extraction

    Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

    Published 2006
    “…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. …”
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  9. 9
    Density subspace clustering: a case study on perception of the required skill

    Density subspace clustering: a case study on perception of the required skill by Sembiring, Rahmat Widia

    Published 2014
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  10. 10
    A genetic-based HAC technique for parallel clustering of bilingual Malay-English corpora

    A genetic-based HAC technique for parallel clustering of bilingual Malay-English corpora by Ng Zhen Wei, Chan Chen Jie, Rayner Alfred, Joe Henry Obit

    Published 2012
    “…Other possible applications include training the algorithm on a hand clustered set of documents, and subsequently applying it to a superset, including unseen documents, incorporating in this way expert knowledge about the domain in the clustering algorithm.…”
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  11. 11
    A framework of modified adaptive neuro-fuzzy inference engine

    A framework of modified adaptive neuro-fuzzy inference engine by Hossen, Md. Jakir

    Published 2012
    “…A modified apriori algorithm was employed to reduce the number of clusters effectively on the basis of common data in the clusters of every input to obtain a minimal set of decision rules based on datasets. …”
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  12. 12
    Modelling kernel methods for unsupervised learning of micro array data

    Modelling kernel methods for unsupervised learning of micro array data by Md. Sap, Mohd. Noor

    Published 2008
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  13. 13
    An evolutionary based features construction methods for data summarization approach

    An evolutionary based features construction methods for data summarization approach by Rayner Alfred, Suraya Alias, Chin, Kim On

    Published 2015
    “…A data summarization approach is proposed due to its capability to learn data stored in multiple tables. …”
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  14. 14
    Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification

    Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification by Mohammed, Alhassan Afnan

    Published 2022
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  15. 15
    Improving The Institutional Research and Publication Performances Using Clustering Algorithm

    Improving The Institutional Research and Publication Performances Using Clustering Algorithm by Mohmad Kamal, Fazillah, Omar, Mohd Faizal, Jamil, Jastini

    Published 2021
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  16. 16
    Analyzing enrolment patterns: modified stacked ensemble statistical learning based approach to educational decision-making

    Analyzing enrolment patterns: modified stacked ensemble statistical learning based approach to educational decision-making by Zun, Liang Chuan, Nursultan Japashov, Soon, Kien Yuan, Tan, Wei Qing, Noriszura Ismail

    Published 2024
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  17. 17
    RECURSIVE LEARNING ALGORITHMS ON RBF NETWORKS FOR NONLINEAR SYSTEM IDENTIFICATION

    RECURSIVE LEARNING ALGORITHMS ON RBF NETWORKS FOR NONLINEAR SYSTEM IDENTIFICATION by CATUR ANDRYANI, NUR AFNY

    Published 2010
    “…This thesis proposes derivative free learning, using finite difference, methods for fixed size RBF network in comparison to gradient based learning for the application of system identification. …”
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  18. 18
    Unsupervised place recognition for assistive mobile robots based on local feature descriptions.

    Unsupervised place recognition for assistive mobile robots based on local feature descriptions. by Tang, Sai Hong, Ramli, Abdul Rahman, Samsudin, Khairulmizam

    Published 2011
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  19. 19
    Development of compound clustering techniques using hybrid soft-computing algorithms

    Development of compound clustering techniques using hybrid soft-computing algorithms by Salim, Naomie, Shamsuddin, Siti Mariyam, Salleh @ Sallehuddin, Roselina, Alwee, Razana

    Published 2006
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  20. 20
    A machine learning approach of predicting high potential archers by means of physical fitness indicators

    A machine learning approach of predicting high potential archers by means of physical fitness indicators by Musa, Rabiu Muazu, Anwar, P. P. Abdul Majeed, Zahari, Taha

    Published 2019
    “…k-nearest neighbour (k-NN) has been shown to be an effective learning algorithm for classification and prediction. …”
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