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  1. 1

    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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    Conference or Workshop Item
  2. 2

    Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems by Mohammad Khamees Khaleel, Alsajri

    Published 2022
    “…Machine learning algorithms have widely been adopted recently to enhance the performance of IDSs. …”
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    Thesis
  3. 3

    Improved intrusion detection algorithm based on TLBO and GA algorithms by Aljanabi, Mohammad, Mohd Arfian, Ismail

    Published 2021
    “…The proposed method combined the New Teaching-Learning-Based Optimization Algorithm (NTLBO), Support Vector Machine (SVM), Extreme Learning Machine (ELM), and Logistic Regression (LR) (feature selection and weighting) NTLBO algorithm with supervised machine learning techniques for Feature Subset Selection (FSS). …”
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    Article
  4. 4
  5. 5

    CSC728 - Machine Learning / College of Computing, Informatics and Media by UiTM, College of Computing, Informatics and Media

    Published 2022
    “…The research in Machine Learning has developed into broad areas of AI, the four main thrusts of research are (1) the improvement of classification accuracy by learning ensembles of classifiers, (2) methods for scaling up supervised learning algorithms, (3) reinforcement learning, and (4) the learning of complex stochastic models."…”
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    Teaching Resource
  6. 6

    CSC728: Machine Learning / College of Computing, Informatics and Mathematics by UiTM, College of Computing, Informatics and Mathematics

    Published 2017
    “…The research in Machine Learning has developed into broad areas of AI, the four main thrusts of research are (1) the improvement of classification accuracy by learning ensembles of classifiers, (2) methods for scaling up supervised learning algorithms, (3) reinforcement learning, and (4) the learning of complex stochastic models."…”
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    Teaching Resource
  7. 7
  8. 8

    Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System by Aljanabi, Mohammad, Mohd Arfian, Ismail, Mezhuyev, Vitaliy

    Published 2020
    “…The proposed method combined the improved teaching-learning-based optimisation (ITLBO) algorithm, improved parallel JAYA (IPJAYA) algorithm, and support vector machine. …”
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    Article
  9. 9

    Evaluation of machine learning in predicting air quality index / Abdullah Sani Abdul Rahman, Aizal Yusrina Idris and Suhaimi Abdul Rahman by Abdul Rahman, Abdullah Sani, Idris, Aizal Yusrina, Abdul Rahman, Suhaimi

    Published 2023
    “…The results show that PM2.5 has the most significant impact on AQI levels among all components analyzed, and all selected machine learning algorithms exhibit high prediction accuracy, with R^ above 90% and low prediction errors (less than 2 MAE and RMSE). …”
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    Article
  10. 10

    Usability prioritization using performance metrics and hierarchical agglomerative clustering in MAR-learning application by Cheng L.K., Selamat A., Mohamed Zabil M.H., Selamat M.H., Alias R.A., Puteh F., Mohamed F., Krejcar O.

    Published 2023
    “…Artificial intelligence; Augmented reality; Cluster analysis; Computer aided instruction; Learning systems; Usability engineering; Agglomerative clustering; English language teaching; Mobile augmented reality; Unsupervised machine learning; Usability; Learning algorithms…”
    Conference Paper
  11. 11

    A WEB-BASED SYSTEM FOR THE PREDICTION OF STUDENT PERFORMANCE IN UPCOMING PUBLIC EXAMS BASED ON ACADEMIC RECORDS by DELLON, NELSON BRUNNIE

    Published 2023
    “…Teachers will be able to precisely forecast their students' impending grades utilizing the system's web-based application integration and machine learning algorithms. The machine learning algorithms that will be used and compared are Support Vector Machines (SVM), Random Forest (RF), K-Nearest Neighbors (KNN), Artificial Neural Network (ANN), and Linear Regression (LR). …”
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    Final Year Project Report / IMRAD
  12. 12

    Teaching and learning via chatbots with immersive and machine learning capabilities by Nantha Kumar Subramaniam

    Published 2019
    “…These chatbots acquired its intelligence through a hybrid approach that combines pattern-matching technique and machine learning algorithm in order to formulate its responses. …”
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    Conference or Workshop Item
  13. 13

    Feasibility comparison of HAC algorithm on usability performance and self-reported metric features for MAR learning by Cheng L.K., Selamat A., Zabil M.H.M., Selamat M.H., Alias R.A., Puteh F., Mohamed F., Krejcar O., Herrera-Viedma E., Fujita H.

    Published 2023
    “…Augmented reality; Cluster analysis; Learning systems; Usability engineering; Agglomerative clustering; English language teaching; Mobile augmented reality; Unsupervised machine learning; Usability; Clustering algorithms…”
    Conference Paper
  14. 14

    Current applications of machine learning in dentistry by Ghazali, Ahmad Badruddin, Reduwan, Nor Hidayah, Ibrahim, Roliana

    Published 2022
    “…Artificial intelligence (AI) is the general description given to computer systems that can perform tasks and mimic the requirement of human intelligence input (Pesapane et al., 2018). Machine learning (ML), a subset of AI was described as an algorithm with the ability to "learn" by identifying patterns in a large dataset (Rowe, 2019). …”
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    Book Chapter
  15. 15

    Examining the potential of machine learning for predicting academic achievement: A systematic review by Nazir, M., Noraziah, Ahmad, Rahmah, M., Sharma, Aditi

    Published 2023
    “…Predicting student academic performance is a critical area of education research. Machine learning (ML) algorithms have gained significant popularity in recent years. …”
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    Article
  16. 16

    Examining the potential of machine learning for predicting academic achievement: A systematic review by Nazir, M., Noraziah, Ahmad, Rahmah, M., Sharma, Aditi

    Published 2023
    “…Predicting student academic performance is a critical area of education research. Machine learning (ML) algorithms have gained significant popularity in recent years. …”
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    Article
  17. 17

    Application of the bees algorithm for constrained mechanical design optimisation problem by Kamaruddin, Shafie, Abd Latif, Mohd Arif Hafizi

    Published 2019
    “…Nowadays, many optimisation algorithms have been introduced due to the advancement of technology such as Teaching Learning Based Optimisation (TLBO), Ant Colony Optimisation (ACO), Particle Swarm Optimisation (PSO) and the Bees Algorithm. …”
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    Article
  18. 18

    E4ML: Alat untuk pembelajaran perlombongan data by Sainin, Mohd Shamrie, Siraj, Fadzilah

    Published 2004
    “…However, most of the tool is complicated to be used by the beginner user especially to student.The absence of specific and easy tool was made the student unable to understand the use and applications in this field.This paper discusses the development of the teaching aid tool (software) that consist of several machine learning algorithms for the purpose of explaining data mining processes.With this tool, teaching and learning for such course can be enhanced in order to provide better understanding in data mining and machine learning.…”
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    Conference or Workshop Item
  19. 19

    Optimization-driven extreme learning machine for floating photovoltaic power prediction: A teaching learning-based approach by Mohd Redzuan, Ahmad, Nor Farizan, Zakaria, Mohd Shawal, Jadin, Mohd Herwan, Sulaiman

    Published 2025
    “…This study presents a novel TeachingLearning-Based Optimization enhanced Extreme Learning Machine (TLBO-ELM) framework that achieves optimal parameter configuration without algorithmic tuning while maintaining computational efficiency for real-time deployment. …”
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    Article
  20. 20

    Research on the construction of English intelligent classroom based on Artificial Intelligence by Wu, Yong, Othman, Abdul Jalil, Saad, Mohd Rashid Mohd

    Published 2018
    “…Due to the uncertainty of emotions, traditional machine learning algorithms may not handle this uncertain inference problem well while probability theory provides us with the basic foundation to model the uncertainty of emotions. …”
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    Article