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  1. 1
    Analytical Study Of Machine Learning Models For Stock Trading In Malaysian Market

    Analytical Study Of Machine Learning Models For Stock Trading In Malaysian Market by Hazirah Halul

    Published 2024
    “…By setting the ML algorithms and their parameter along with using Walk-Forward Analysis (WFA) method, the algorithm design of trading signal was evaluated based on two groups of evaluation indicators, namely directional and performance. …”
    thesis::master thesis
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  2. 2
    Clustering ensemble learning method based on incremental genetic algorithms

    Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

    Published 2012
    “…In order to address the above mentioned challenges, this study is devoted towards the development of a clusterer and a clustering ensemble learning method based on incremental genetic algorithms addressing group unlabeled samples. …”
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  3. 3
    A new fuzzy peer assessment methodology for cooperative learning of students

    A new fuzzy peer assessment methodology for cooperative learning of students by Tay, Kai Meng, Kok, Chin Chai, Chee, Peng Lim

    Published 2015
    “…The outcomes clearly demonstrate that the proposed fuzzy peer assessment methodology can be deployed as an effective evaluation tool for cooperative learning of students.…”
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  4. 4
    A dynamic eLearning prediction modelbased on incomplete activities of eLearning system

    A dynamic eLearning prediction modelbased on incomplete activities of eLearning system by Chayanukro, Songsakda

    Published 2020
    “…Six data mining algorithms were used in evaluating the model. The results found seven significant groups of eLearning activities that could predict the learning outcome with more than 75% accuracy. …”
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  5. 5
    A comprehensive comparison of recent developed meta-heuristic algorithms for streamflow time series forecasting problem

    A comprehensive comparison of recent developed meta-heuristic algorithms for streamflow time series forecasting problem by Ahmed A.N., Van Lam T., Hung N.D., Van Thieu N., Kisi O., El-Shafie A.

    Published 2023
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  6. 6
    Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224)

    Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224) by Mahat, Nor Idayu, Engku Abu Bakar, Engku Muhammad Nazri, Zakaria, Ammar, Mohd Nazir, Mohd Amril Nurman, Misiran, Masnita

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    Monograph
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  7. 7
    Algorithm-program visualization model : An intergrated software visualzation to support novices' programming comprehension

    Algorithm-program visualization model : An intergrated software visualzation to support novices' programming comprehension by Affandy

    Published 2015
    “…The programming performances from the treatment and control group are compared to analyze the effect of using the proposed tool in learning programming. …”
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  8. 8
    The implications for ahybrid detection technique against malicious sqlattacks on web applications

    The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

    Published 2025
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  9. 9
    Prediction of biochemical oxygen demand in Mexican surface waters using machine learning / Maximiliano Guzmán-Fernández ... [et al.]

    Prediction of biochemical oxygen demand in Mexican surface waters using machine learning / Maximiliano Guzmán-Fernández ... [et al.] by Maximiliano, Guzmán-Fernández, Misael, Zambrano-de la Torre, Claudia, Sifuentes-Gallardo, Oscar, Cruz-Dominguez, Carlos, Bautista-Capetillo, Juan, Badillo-de Loera, Efrén, González Ramírez, Héctor, Durán-Muñoz

    Published 2021
    “…Pearson’s correlation and Forward Selection techniques were applied to identify the parameters with the most important contribution to prediction of biochemical oxygen demand. Two groups were formed and used as input to four machine learning algorithms. …”
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  10. 10
    Assessing the potential of laboratory instructional tool through Synthesia AI: a case study on student learning outcome / Jacqueline Joseph

    Assessing the potential of laboratory instructional tool through Synthesia AI: a case study on student learning outcome / Jacqueline Joseph by Joseph, Jacqueline

    Published 2023
    “…The research focused on evaluating the impact of incorporating Synthesia AI as a supplementary learning resource on student learning outcomes in laboratory settings. …”
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  11. 11
    The impact of executive function and aerobic exercise recognition in obese children under deep learning

    The impact of executive function and aerobic exercise recognition in obese children under deep learning by JING, XIN, ABDULLAH, BORHANNUDIN, ABU SAAD, HAZIZI, YANG, XIANGKUN

    Published 2025
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  12. 12
    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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  13. 13
    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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  14. 14
    Simulation model algorithm for pre-hospital emergency care (PHEC) volunteers in Indonesia

    Simulation model algorithm for pre-hospital emergency care (PHEC) volunteers in Indonesia by Martono, Martono, Sudiro, Sudiro, Satino, Satino

    Published 2018
    “…Algorithm models for PHEC simulation have some strengths in real setting and effective interactive learning to evaluate the capabilities of first responders in managing pre-hospital emergency, and improve problem-solving skills, as well as their performance in such aspects as skill, knowledge, and attitude.…”
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  15. 15
    Evaluation of machine learning classifiers in faulty die prediction to maximize cost scrapping avoidance and assembly test capacity savings in semiconductor integrated circuit (IC) manufacturing

    Evaluation of machine learning classifiers in faulty die prediction to maximize cost scrapping avoidance and assembly test capacity savings in semiconductor integrated circuit (IC)... by Mohd Fazil, Azlan Faizal, Mohd Shaharanee, Izwan Nizal, Mohd Jamil, Jastini

    Published 2019
    “…The control group will serve as reference. The other group, will use auto machine learning (ML) to run multiple classifiers automatically and only top 3 to be selected for next step. …”
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  16. 16
    Cognitive knowledge-based model for adaptive feedback: A case in physics / Andrew Thomas Bimba

    Cognitive knowledge-based model for adaptive feedback: A case in physics / Andrew Thomas Bimba by Andrew Thomas, Bimba

    Published 2019
    “…In comparing three experimental groups, students who were provided with adaptive feedback showed learning gains and normalized learning gains of 0.87 and 0.05 over the normal feedback group, with 0.97 and 0.07 over the non-feedback group. …”
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  17. 17
    Windows-Based bandwidth allocation on optical networks

    Windows-Based bandwidth allocation on optical networks by Mahadevan, V., Yu, W., Zhou, J.

    Published 2009
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  18. 18
    A cognitive mapping approach in real-time haptic rendering interaction for improved spatial learning ability among autistic people / Kesavan Krishnan

    A cognitive mapping approach in real-time haptic rendering interaction for improved spatial learning ability among autistic people / Kesavan Krishnan by Kesavan , Krishnan

    Published 2024
    “…Meanwhile, experimental evaluation of the application was conducted in four different groups to measure the efficiency and performance of the application; experimental evaluation based on navigation algorithms, experimental evaluation based on haptic sensory sensitivity, experimental evaluation based on real-time haptic rendering interaction and experimental evaluation based on the performance of autistic people with using the application in spatial learning and cognitive mapping. …”
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  19. 19
    A Reinforced Active Learning Algorithm for Semantic Segmentation in Complex Imaging

    A Reinforced Active Learning Algorithm for Semantic Segmentation in Complex Imaging by Usmani, U.A., Watada, J., Jaafar, J., Aziz, I.A., Roy, A.

    Published 2021
    “…We propose a new reinforced active learning strategy based on a deep reinforcement learning algorithm. …”
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  20. 20
    Diabetic disease classifier based on three machine learning models / ‘Ayuni Zamri ... [et al.]

    Diabetic disease classifier based on three machine learning models / ‘Ayuni Zamri ... [et al.] by Zamri, ‘Ayuni, Darmawan, Mohd Faaizie, Mohamed Hatim, Shahirah, Zainal Abidin, Ahmad Firdaus, Osman, Mohd Zamri

    Published 2022
    “…The aim of this research is to aid the medical professionals to diagnose patients whether the patients is diabetic or not diabetic, by applying machine learning algorithms, and evaluate the results to find the best algorithm to predict diabetic diseases. …”
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