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  1. 1
    Autism Spectrum Disorder Classification Using Deep Learning

    Autism Spectrum Disorder Classification Using Deep Learning by Abdulrazak Yahya, Saleh, Lim Huey, Chern

    Published 2021
    “…Recently, deep learning methods have significantly sharpened the cutting edge of learning algorithms in a wide range of artificial intelligence tasks. …”
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  2. 2
    Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool

    Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool by Nurshafiqa Saffah, Mohd Sharif

    Published 2018
    “…No EEG studies in Malaysia has been done on school children to study their emotional behaviour while learning. Classification and prediction are the functions provided by the data mining techniques that suit in EEG signal processing. …”
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  3. 3
    Genetic ensemble biased ARTMAP method of ECG-Based emotion classification

    Genetic ensemble biased ARTMAP method of ECG-Based emotion classification by Loo, C.K., Liew, W.S., Sayeed, M.S.

    Published 2012
    “…Classification performance can be improved by implementing a reliability threshold for training data. …”
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  4. 4
    An Empirical Evaluation of Artificial Intelligence Algorithm for Hand Posture Classification

    An Empirical Evaluation of Artificial Intelligence Algorithm for Hand Posture Classification by Hussain, A., Hussain, S.S., Uddin, M.M., Zubair, M., Kumar, P., Umair, M.

    Published 2022
    “…In this study, exhaustive empirical research of the machine learning algorithm for hand posture classification has been established. …”
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  5. 5
    Identifying the correct articulation point of a Quranic letters of the throat (al-halqu) makhraj

    Identifying the correct articulation point of a Quranic letters of the throat (al-halqu) makhraj by Othman, Ahmad Al Baqir, Ahmad, Salmiah, Badron, Khairayu, Altalmas, Tareq M. K.

    Published 2023
    “…Data was trained using an improved deep learning Convolutional Neural Network (CNN) classification model. …”
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  6. 6
    Predictive analytics for the sentiment of malaysian place of interest using machine learning models

    Predictive analytics for the sentiment of malaysian place of interest using machine learning models by Qiryn Adriana, Kharul Zaman

    Published 2023
    “…The focus of this study is to conduct Natural Language Processing (NLP) on tweets and make a better classification of sentiment using Malaya. Furthermore, this study also trains three machine learning algorithms to predict the sentiment of textual data. …”
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    Undergraduates Project Papers
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  7. 7
    A Review: Recent Automatic Algorithms for the Segmentation of Brain Tumor MRI

    A Review: Recent Automatic Algorithms for the Segmentation of Brain Tumor MRI by Rafi, A., Khan, Z., Aslam, F., Jawed, S., Shafique, A., Ali, H.

    Published 2022
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  8. 8
    An enhancement of age and gender classification accuracy with hybrid handcrafted and deep features using hierarchical extreme learning machine / Mohammad Javidan Darugar

    An enhancement of age and gender classification accuracy with hybrid handcrafted and deep features using hierarchical extreme learning machine / Mohammad Javidan Darugar by Mohammad Javidan , Darugar

    Published 2020
    “…Age and gender classification are some of the essential algorithms that have many use cases in our everyday life. …”
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  9. 9
    Improving multi-resident activity recognition in smart home using multi label classification with adaptive profiling

    Improving multi-resident activity recognition in smart home using multi label classification with adaptive profiling by Mohamed, Raihani

    Published 2018
    “…On top of that, data association and algorithm modification inherit drawbacks on recognizing the residents and interactions of multi-resident complex activities. …”
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  10. 10
    Characterizing land use/land cover change dynamics by an enhanced random forest machine learning model: a Google Earth Engine implementation

    Characterizing land use/land cover change dynamics by an enhanced random forest machine learning model: a Google Earth Engine implementation by Pande C.B., Srivastava A., Moharir K.N., Radwan N., Mohd Sidek L., Alshehri F., Pal S.C., Tolche A.D., Zhran M.

    Published 2025
    “…A novel multiple composite RF approach based on LULC classification was utilized to generate the final LULC classification maps utilizing the RF-50 and RF-100 tree models. …”
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  11. 11
    Case Slicing Technique for Feature Selection

    Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

    Published 2004
    “…One of the problems addressed by machine learning is data classification. Finding a good classification algorithm is an important component of many data mining projects. …”
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  12. 12
    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition

    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

    Published 2017
    “…Whereas for supervised learning method, it requires teacher or prior data (i.e. large, prohibitive and labelled training data) during classification process which in real life, the cost of obtaining sufficient labelled training data is high. …”
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  13. 13
    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model

    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…In data mining, classification learning is broadly categorized into two categories; supervised and unsupervised. …”
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  14. 14
    Mean of correlation method for optimization of affective states detection in children

    Mean of correlation method for optimization of affective states detection in children by Rusli, Nazreen, Sidek, Shahrul Na'im, Md Yusuf, Hazlina, Ishak, Nor Izzati

    Published 2018
    “…At the moment, most of the studies on classification of affective states for children focus on visual observations and physiological cues, where all data collection for measuring physiological signals are contact-based and invasive. …”
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  15. 15
    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
    “…Feature selection and classification are widely utilized for data analysis. …”
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  16. 16
    Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach

    Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach by Moheb Pour, Majid Reza

    Published 2009
    “…The two algorithms were compared, and the proposed algorithm was found to be able to both learn and classify quickly. …”
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  17. 17
    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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  18. 18
    Performances of machine learning algorithms for binary classification of network anomaly detection system

    Performances of machine learning algorithms for binary classification of network anomaly detection system by Nawir, M., Amir, A., Lynn, O.B., Yaakob, N., Ahmad, R.B.

    Published 2018
    “…Moreover, network anomaly detection using machine learning faced difficulty when dealing the involvement of dataset where the number of labelled network dataset is very few in public and this caused many researchers keep used the most commonly network dataset (KDDCup99) which is not relevant to employ the machine learning (ML) algorithms for a classification. …”
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  19. 19
    Comparative study of machine learning algorithms in data classification

    Comparative study of machine learning algorithms in data classification by Tan, Kai Jun

    Published 2025
    “…This research conducts a comparative study of various machine learning algorithms for dataset classification to identify the most accurate and reliable classifier. …”
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    Final Year Project / Dissertation / Thesis
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  20. 20
    Evaluation of the Transfer Learning Models in Wafer Defects Classification

    Evaluation of the Transfer Learning Models in Wafer Defects Classification by Jessnor Arif, Mat Jizat, Anwar, P. P. Abdul Majeed, Ahmad Fakhri, Ab. Nasir, Zahari, Taha, Yuen, Edmund, Lim, Shi Xuen

    Published 2022
    “…Transfer Learning is one of the common methods. Various algorithms under Transfer Learning had been developed for different applications. …”
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