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  1. 1
    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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  2. 2
    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
    “…The optimal combination of λ and training sequence can be computed efficiently using a genetic permutation algorithm. The best combinations were selected to train individual ARTMAPs as voting members, and the final class predictions were determined using probabilistic ensemble voting strategy. …”
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    Conference or Workshop Item
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  3. 3
    Identifying Cyberspace Users� Tendency in Blog Writing Using Machine Learning Algorithms

    Identifying Cyberspace Users� Tendency in Blog Writing Using Machine Learning Algorithms by AbuSalim, S.W.G., Mostafa, S.A., Mustapha, A., Ibrahim, R., Wahab, M.H.A.

    Published 2023
    “…In this paper, we use an existing data set from previous research, which has 100 records of data, and manipulate the data by applying three machine learning algorithms for implementing classification and regression tasks. …”
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  4. 4
    Simulation on Emotion Recognition for Autism Therapy

    Simulation on Emotion Recognition for Autism Therapy by Adzmi, Muhammad Azrin

    Published 2017
    “…The program will be used by the therapist during therapy session with the autism child in order to create more exciting environment for them to learn about the classification of basic human emotions with the help of human-computer interaction. …”
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    Final Year Project
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  5. 5
    Spiking Neural Network For Energy Efficient Learning And Recognition

    Spiking Neural Network For Energy Efficient Learning And Recognition by Wong, Yan Chiew, Wang, Ning Lo

    Published 2020
    “…The use of applications consumes energy and hard to perform through standard programmed algorithms. …”
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  6. 6
    Classification Modeling for Malaysian Blooming Flower Images Using Neural Networks

    Classification Modeling for Malaysian Blooming Flower Images Using Neural Networks by Muhammad Ashraq, Salahuddin

    Published 2013
    “…In training and testing phases, experiments were carried out to observe the classification performance of Neural Networks with duplication of difficult pattern to learn (referred to as DOUBLE) as this could possibly explain as to why some flower images were difficult to learn by classifiers. …”
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    Thesis
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  7. 7
    Pattern classification of human interactions from videos / Muhsin Abdul Mohammed

    Pattern classification of human interactions from videos / Muhsin Abdul Mohammed by Muhsin , Abdul Mohammed

    Published 2018
    “…In order to build a classifier capable of achieving this task, the machine learning model needs to be able to learn spatial and temporal patterns from the videos. …”
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    Thesis
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  8. 8
    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
    “…This paper proposes an effective algorithm of texture analysis based on novel technique using Gray Level Co-occurrence Matrix approach to be applied so as to identify blood-flow region. …”
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  9. 9
    Using Pattern Matching technique for feature recognition of STEP file

    Using Pattern Matching technique for feature recognition of STEP file by Nik Norhazlina Nik Hassan

    Published 2008
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    Learning Object
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  10. 10
    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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    Thesis
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  11. 11
    CT-eKit: computational thinking interactive learning / Ong Sing Ling, Jill Ling and Fetylyana Nor Pazilah

    CT-eKit: computational thinking interactive learning / Ong Sing Ling, Jill Ling and Fetylyana Nor Pazilah by Ong, Sing Ling, Jill, Ling, Pazilah, Fetylyana Nor

    Published 2023
    “…The CT-eKit consists of three main activities: a CT video, a Kahoot CT quiz and a Scratch CT Concepts game to learn the four CT concepts: decompose, pattern, abstraction and algorithm in a fun and interactive environment. …”
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    Book Section
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  12. 12
    Machine learning using robust AI techniques / Prof. Madya Dr. Nordin Abu Bakar

    Machine learning using robust AI techniques / Prof. Madya Dr. Nordin Abu Bakar by Abu Bakar, Nordin (Prof. Madya Dr.)

    Published 2012
    “…Many algorithms have been applied to aid the assessment process. …”
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    Research Reports
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  13. 13
    An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani

    An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani by Ab Ghani, Nur Laila

    Published 2015
    “…The urban growth images obtained are analysed to improve existing classification algorithms. The improved algorithm is constructed by adding new parameter and classification rule to existing algorithm. …”
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    Thesis
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  14. 14
    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms

    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

    Published 2005
    “…The comparison showed that, the accuracy of the unsupervised classification map with value of 88.4% that was generated by using the cluster labelling algorithm was slightly more than the maximum-likelihood supervised classification map with value of 87.5%. …”
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    Thesis
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  15. 15
    Dengue classification system using clonal selection algorithm / Karimah Mohd

    Dengue classification system using clonal selection algorithm / Karimah Mohd by Mohd, Karimah

    Published 2012
    “…This project can be improved by making a comparative study on Artificial Immune System and other techniques or algorithms used to solve dengue classification problems.…”
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    Thesis
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  16. 16
    Immune network algorithm in monthly streamflow prediction at Johor river

    Immune network algorithm in monthly streamflow prediction at Johor river by Mat Ali, Nur Izzah, Abdul Malik, Marlinda, Ismail , Amelia Ritahani

    Published 2014
    “…The model of Immune Network Algorithm used in this study is aiNet. The training process in aiNet is partly inspired by clonal selection principle and the other part uses antibody interactions for removing redundancy and finding data patterns. …”
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    Proceeding Paper
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  17. 17
    Classification of tropical rainforest using different classification algorithm based on remote sensing imagery: A study of Gunung Basor

    Classification of tropical rainforest using different classification algorithm based on remote sensing imagery: A study of Gunung Basor by Intan Noradybah Md Rodi

    Published 2019
    “…Thehighest accuracy for classification map of Gunung Basor is by using maximum likelihood algorithm with an accuracy of 82.90%. …”
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    Undergraduate Final Project Report
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  18. 18
    ABC: android botnet classification using feature selection and classification algorithms

    ABC: android botnet classification using feature selection and classification algorithms by Abdullah, Zubaile, Mohd Saudi, Madihah, Anuar, Nor Badrul

    Published 2017
    “…The Information Gain algorithm is used to select the most significant permissions, then the classification algorithms Naïve Bayes, Random Forest and J48 used to classify the Android apps as botnet or benign apps. …”
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  19. 19
    Case Slicing Technique for Feature Selection

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

    Published 2004
    “…Case Slicing Technique (CST) helps in identifying the subset of features used in computing the similarity measures needed by classification algorithms. …”
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    Thesis
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  20. 20
    Development of a fingerprint gender classification algorithm using fingerprint global features

    Development of a fingerprint gender classification algorithm using fingerprint global features by Abdullah, Siti Fairuz, Abdul Rahman, Ahmad Fadzli Nizam, Abal Abas, Zuraida, Mohd Saad, Wira Hidayat

    Published 2016
    “…This algorithm is highly recommended in extracting a fingerprint global feature for gender classification process.…”
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