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  1. 1
    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly

    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

    Published 2019
    “…Iris data set has been taken from UCO machine learning to assist in testing phase. …”
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  2. 2
    Multiview Laplacian semisupervised feature selection by leveraging shared knowledge among multiple tasks

    Multiview Laplacian semisupervised feature selection by leveraging shared knowledge among multiple tasks by Krishnasamy, Ganesh, Paramesran, Raveendran

    Published 2019
    “…However, these semisupervised multitask selection feature algorithms are unable to naturally handle the multiview data since they are designed to deal single-view data. …”
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  3. 3
    Machine Learning Algorithms for Diabetes Prediction: A Review Paper

    Machine Learning Algorithms for Diabetes Prediction: A Review Paper by Al-Sideiri A., Cob Z.B.C., Drus S.B.M.

    Published 2023
    “…Computer aided diagnosis; Data mining; Learning systems; Patient treatment; Predictive analytics; Robotics; Support vector machines; Data mining algorithm; Diabetes mellitus; Early diagnosis; Knowledge accumulation; Literature reviews; Prediction techniques; Review papers; Support vector machine algorithm; Learning algorithms…”
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  4. 4
    A Truly Online Learning Algorithm using Hybrid Fuzzy ARTMAP and Online Extreme Learning Machine for Pattern Classification

    A Truly Online Learning Algorithm using Hybrid Fuzzy ARTMAP and Online Extreme Learning Machine for Pattern Classification by Wong S.Y., Yap K.S., Yap H.J., Tan S.C.

    Published 2023
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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
    “…In these experiments, all the training and testing data are represented as feature vectors. By using the proposed algorithm, the sparse coefficients are learned by exploiting the relationships among different multi-view features and leveraging the knowledge from multiple related tasks. …”
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  6. 6
    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process

    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process by Ali Al-Assadi, Hayder M. A.

    Published 2004
    “…The design network is trained by presenting several target machining data that the network must learn according to a learning rule (algorithm). …”
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  7. 7
    Reliability fuzzy clustering algorithm for wellness of elderly people

    Reliability fuzzy clustering algorithm for wellness of elderly people by N. J., Mohd Jamal, Ku Muhammad Naim, Ku Khalif, Mohd Sham, Mohamad

    Published 2019
    “…Fuzzy clustering is one of the unsupervised machine learning techniques based knowledge of data analysis that automated or semi-automated analytical model building. …”
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  8. 8
    E4ML: Educational Tool for Machine Learning

    E4ML: Educational Tool for Machine Learning by Sainin, Mohd Shamrie, Siraj, Fadzilah

    Published 2003
    “…There are various types of machine learning algorithms with certain processes taken by the algorithm.In teaching of the machine learning algorithms, such processes need to be explained especially to the beginner in introductory level.This paper discusses the development the tool that addresses the process by certain algorithm to produce a hypothesis or output based on given data.This tool can also be used in teaching and learning purposes.The explanation of processes by the algorithms is demonstrated through simple simulation.The source of the algorithms was adapted from Mitchell book [1] that cover popular algorithms in machine learning for teaching and learning such as Concept Learning, Decision Tree, Bayesian Learning, Neural Networks, and Instance based Learning.The tool also used several classes of Weka (Waikato Environment for Knowledge Analysis) as a basis for the design and implementation of the new tool that focuses on explaining the processes taken by certain algorithm.…”
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  9. 9
    Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things

    Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

    Published 2022
    “…Thus, using neural network-based semi-supervised stream data learning is inadequate due to capture the changes in the distribution and characteristics of various classes of data while avoiding the effect of the outdated stored knowledge in neural networks (NN). …”
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  10. 10
    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
    “…Data mining is a widely used approach for knowledge discovery in machine learning. …”
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  11. 11
    Employing machine learning algorithms to extract Islamic knowledge

    Employing machine learning algorithms to extract Islamic knowledge by Aldhlan, Kawther A., Zeki, Ahmed M., Zeki, Akram M.

    Published 2011
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  12. 12
    Optimal route checking using genetic algorithm for UiTM's bus services / Tengku Salman Fathi Tengku Jaafar

    Optimal route checking using genetic algorithm for UiTM's bus services / Tengku Salman Fathi Tengku Jaafar by Tengku Jaafar, Tengku Salman Fathi

    Published 2006
    “…Although from human logical thinking, the route can be generated easily but the calculation of checking the route whether it is optimal route or not is difficult and will take long time to be implemented. This research study with the development of the Optimal Route Checking Using Genetic Algorithm system should solve this scenario. …”
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  13. 13
    Development of intelligent hybrid learning system using clustering and knowledge-based neural networks for economic forecasting : First phase

    Development of intelligent hybrid learning system using clustering and knowledge-based neural networks for economic forecasting : First phase by Che Mat @ Mohd Shukor, Zamzarina, Md Sap, Mohd Noor

    Published 2004
    “…We proposed KMeans clustering algorithm that is based on multidimensional scaling, joined with neural knowledge based technique algorithm for supporting the learning module to generate interesting clusters that will generate interesting rules for extracting knowledge from stock exchange databases efficiently and accurately.…”
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  14. 14
    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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  15. 15
    Sentiment mining using immune network algorithm /Raja Muhammad Hafiz Raja Kamarudin

    Sentiment mining using immune network algorithm /Raja Muhammad Hafiz Raja Kamarudin by Raja Kamarudin, Raja Muhammad Hafiz

    Published 2012
    “…The results obtained by utilizing Immune Network in sentiment mining are not very impressive compared to other Machine Learning algorithms. The algorithms can be improved furthermore by including other disciplines such as Natural Language Processing (NLP) or others. …”
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  16. 16
    An Improvement on Extended Kalman Filter for Neural Network Training

    An Improvement on Extended Kalman Filter for Neural Network Training by Tsan, Ken Yim

    Published 2005
    “…Extracting useful imformation and knowledge from data is a major concern in information science. …”
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  17. 17
    Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer

    Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer by Tuerxun, Adilijiang

    Published 2017
    “…Furthermore, the Lazy-IBK algorithm have been validated to produce the best classifier model, with the machine learning algorithm performance of 65.26%, recall of 65.3%, and 65.4% F-measured as compared to other evaluated machine learning classifier algorithms proposed within the WEKA data mining algorithm. …”
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  18. 18
    A Truly Online Learning Algorithm using Hybrid Fuzzy ARTMAP and Online Extreme Learning Machine for Pattern Classification

    A Truly Online Learning Algorithm using Hybrid Fuzzy ARTMAP and Online Extreme Learning Machine for Pattern Classification by Wong, S.Y., Yap, K.S., Yap, H.J., Tan, S.C.

    Published 2015
    “…This paper presents a Hybrid Fuzzy ARTMAP (FAM) and Online Extreme learning machine (OELM), hereafter denoted as FAM-OELM, which enables online learning to start from the first trained data samples without having to set up an initialization phase which requires a chunk of data samples to be ready prior to training. …”
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  19. 19
    Multi-Backpropagation network

    Multi-Backpropagation network by Wan Ishak, Wan Hussain, Siraj, Fadzilah, Othman, Abu Talib

    Published 2002
    “…In most cases, Neural Network considered large amount of data, as it will be teach to learn or memorize the data as the knowledge. …”
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  20. 20
    Advancements and challenges in mobile robot navigation: a comprehensive review of algorithms and potential for self-learning approaches

    Advancements and challenges in mobile robot navigation: a comprehensive review of algorithms and potential for self-learning approaches by Al Mahmud, Suaib, Kamarulariffin, Abdurrahman, Mohd Ibrahim, Azhar, Haja Mohideen, Ahmad Jazlan

    Published 2024
    “…In this review paper, a comprehensive review of mobile robot navigation algorithms has been conducted. The findings suggest that, even though the self-learning algorithms require huge amounts of training data and have the possibility of learning erroneous behavior, they possess huge potential to overcome challenges rarely addressed by the other traditional algorithms. …”
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