Search Results - (( using factorization learning algorithm ) OR ( pattern classifications using algorithm ))

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    Survival versus non-survival prediction after acute coronary syndrome in Malaysian population using machine learning technique / Nanyonga Aziida by Nanyonga , Aziida

    Published 2019
    “…Combinations of feature selection and classification algorithms were used for mortality prediction post ACS. …”
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    Thesis
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    Classification of Students' Performance in Computer Programming Course According to Learning Style by Norwawi, NM, Abdusalam, SF, Hibadullah, CF, Shuaibu, BM

    Published 2024
    “…Previous studies examined some of the variables influencing students' performance using statistical data analysis. The critical point of this study is the use of classification algorithm to extract patterns which are examined from the cognitive factor specific learning style. …”
    Proceedings Paper
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    Prediction of sleep pattern for university students using machine learning by Widya, Muhammad Faishal Atha, Utoro, Rio Korio, Roedavan, Rickman, Soegiarto, Duddy, Moorthy, Kohbalan, Pratondo, Agus

    Published 2026
    “…This study aims to predict sleep patterns among university students using machine learning techniques, focusing on the classification of regular and irregular sleep behaviors. …”
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    Conference or Workshop Item
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    Backpropagation algorithm for classification problem: academic performance prediction model for UiTM Melaka Mengubah Destini Anak Bangsa (MDAB) program. / Fadhlina Izzah Saman, Nur... by Saman, Fadhlina Izzah, Zainuddin, Nurulhuda, Md Shahid, Khairiyah

    Published 2012
    “…Multilayer perceptrons (MLPs) is one of the topology used for processing ANN, while backpropagation algorithm is one of the most popular methods in training MLPs. …”
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    Research Reports
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    Development of an intelligent system using Kernel-based learning methods for predicting oil-palm yield. by Md. Sap, Mohd. Noor, Awan, A. Majid

    Published 2005
    “…The proposed algorithm can effectively handle noise, outliers and auto-correlation in the spatial data, for effective and efficient data analysis by exploring patterns and structures in the data, and thus can be used for predicting oil-palm yield by analyzing various factors affecting oil-palm yield.…”
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    Article
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    Classification of stock market index based on predictive fuzzy decision tree by Khokhar, Arashid Hafeez

    Published 2005
    “…In particular, predictive FDT algorithm is based on the concept of degree of importance of attribute contributing to the classification. …”
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    Household overspending model amongst B40, M40 and T20 using classification algorithm by Zulaiha Ali, Othman, Azuraliza, Abu Bakar, Nor Samsiah, Sani, Jamaludin, Sallim

    Published 2020
    “…The model development employs five machine learning algorithms namely decision tree, Naive Bayes, Neural network, Support Vector Machines, Nearest Neighbour. …”
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    Article
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    A framework for predicting oil-palm yield from climate data by Awan, A. Majid, Md. Sap, Mohd. Noor

    Published 2006
    “…The proposed algorithm can effectively handle noise, outliers and auto-correlation in the spatial data, for effective and efficient data analysis by exploring patterns and structures in the data, and thus can be used for predicting oil-palm yield by analyzing various factors affecting the yield.…”
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    Conference or Workshop Item
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    Neurons to heartbeats: spiking neural networks for electrocardiogram pattern recognition by Wong, Yan Chiew, Mohamad Noor, Nor Amalia Dayana, Mohd Noh, Zarina, Sarban Singh, Ranjit Singh

    Published 2024
    “…Establishing functioning spiking neural networks (SNN) involves figuring out the neuron’s state through its activity level, challenging due to its resemblance to the human brain’s data processing, yet appealing due to factors like improved unsupervised learning methods, with ten parameters chosen for the learning algorithm of SNN. …”
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    Article
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    Raspberry Pi-Based Finger Vein Recognition System Using PCANet by Quek, Ee Wen

    Published 2018
    “…For classification, k-Nearest Neighbours (kNN) with Euclidean distance algorithm is implemented. …”
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    Monograph
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    The effect of pre-processing techniques and optimal parameters on BPNN for data classification by HUSSEIN, AMEER SALEH

    Published 2015
    “…Most existing approaches modify the learning model in order to add a random factor to the model which can help to overcome the tendency to sink into local minima. …”
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    Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach by Mustakim, Nurul Ain

    Published 2025
    “…The descriptive analysis examines purchasing behavior through correlation and regression analyses, while the predictive model uses decision trees (J48, Random Tree, REPTree), rule-based algorithms (JRip, OneR, PART), and clustering (K-Means) to identify patterns and predict trends. …”
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    Thesis
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    Machine Learning-Based Stress Level Detection from EEG Signals by Nirabi, Ali, Abd Rhman, Faridah, Habaebi, Mohamed Hadi, Sidek, Khairul Azami, Yusoff, Siti Hajar

    Published 2021
    “…Stress is associated with the brain activities of human beings that can be scanned by electroencephalogram (EEG) signals which is very complex and often challenging to understand the signal's pattern. This paper presented a system to detect the stress level from the EEG signals using machine learning algorithms. …”
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    Proceeding Paper
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    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

    Published 2017
    “…In pattern recognition system, achieving high accuracy in pattern classification is crucial. …”
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    Thesis