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  1. 1
    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
    “…In pattern recognition system, achieving high accuracy in pattern classification is crucial. …”
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  2. 2
    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
    “…Meanwhile, Kmeans clustering algorithm has also been reported has widely known for solving most unsupervised classification problems. …”
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  3. 3
    Biceps brachii surface EMG classification using neural networks

    Biceps brachii surface EMG classification using neural networks by Chong, Yee Lin

    Published 2012
    “…With these satisfactory results, the effectiveness of the proposed classifiers in EMG pattern classification problem is proven.…”
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  4. 4
    An improved multiple classifier combination scheme for pattern classification

    An improved multiple classifier combination scheme for pattern classification by Abdullah,

    Published 2015
    “…Combining multiple classifiers are considered as a new direction in the pattern recognition to improve classification performance. …”
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  5. 5
    Correlation-based common spatial pattern (CCSP): A novel extension of CSP for classification of motor imagery signal

    Correlation-based common spatial pattern (CCSP): A novel extension of CSP for classification of motor imagery signal by Khatereh Darvish ghanbar, Tohid Yousefi Rezaii, Ali Farzamnia, Ismail Saad

    Published 2021
    “…The simulation results showed that the proposed method outperformed conventional CSP by 6.9% in 2-class and 2.23% in multi-class problem in term of mean classification accuracy.…”
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  6. 6
    Development of a new robust hybrid automata algorithm based on surface electromyography (SEMG) signal for instrumented wheelchair control

    Development of a new robust hybrid automata algorithm based on surface electromyography (SEMG) signal for instrumented wheelchair control by Mohd Hanafi, Muhammad Sidik

    Published 2020
    “…Addition of hybrid automata algorithm to run pattern and non-pattern recognition based control methods is an advantage to increase accuracy in differentiating forward stroke or hand return activity. …”
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  7. 7
    Neuro fuzzy classification and detection technique for bioinformatics problems

    Neuro fuzzy classification and detection technique for bioinformatics problems by Othman, Mohd. Fauzi, Moh, Thomas Shan Yau

    Published 2007
    “…It is very important to identify new integration of classification or clustering algorithm especially in neuro fuzzy domain as compared to conventional or traditional method. …”
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  8. 8
    A framework of modified adaptive neuro-fuzzy inference engine

    A framework of modified adaptive neuro-fuzzy inference engine by Hossen, Md. Jakir

    Published 2012
    “…The performance of MANFIE was compared with existing methods in a diversity of practical benchmark applications such as pattern classifications, time series predictions, modeling with inverse learning control and mobile robot navigation. …”
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  9. 9
    Ant system-based feature set partitioning algorithm for classifier ensemble construction

    Ant system-based feature set partitioning algorithm for classifier ensemble construction by Abdullah, , Ku-Mahamud, Ku Ruhana

    Published 2016
    “…Ensemble method is considered as a new direction in pattern classification. Accuracy and diversity in a set of classifiers are two important things to be considered in constructing classifier ensemble.Several approaches have been proposed to construct the classifier ensemble. …”
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  10. 10
    A global k-means approach for autonomous cluster initialization of probabilistic neural network

    A global k-means approach for autonomous cluster initialization of probabilistic neural network by Chang, R.K.Y., Loo, C.K., Rao, M.V.C.

    Published 2008
    “…This paper focuses on the statistical based Probabilistic Neural Network (PNN) for pattern classification problems with Expectation â�� Maximization (EM) chosen as the training algorithm. …”
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  11. 11
    Predicting building damage grade by earthquake: a Bayesian Optimization-based comparative study of machine learning algorithms

    Predicting building damage grade by earthquake: a Bayesian Optimization-based comparative study of machine learning algorithms by Al-Rawashdeh, Mohammad, Al Nawaiseh, Moh’d, Yousef, Isam, Bisharah, Majdi, Alkhadrawi, Sajeda, Al-Bdour, Hamza

    Published 2024
    “…Bayesian Optimization helps models acquire data patterns, improving classification accuracy. This study shows that machine learning and optimization can forecast building seismic damage grades. …”
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  12. 12
    Comparative analysis for topic classification in juz Al-Baqarah

    Comparative analysis for topic classification in juz Al-Baqarah by Rahman, Mohamad Izzuddin, Samsudin, Noor Azah, Mustapha, Aida, Abdullahi Oyekunle, Adeleke

    Published 2018
    “…The SVM performance is then compared against other classification algorithms such as Naive Bayes, J48 Decision Tree and K-Nearest Neighbours. …”
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  13. 13
    Comprehensive review of retinal blood vessel segmentation and classification techniques: intelligent solutions for green computing in medical images, current challenges, open issues, and knowledge gaps in fundus medical images

    Comprehensive review of retinal blood vessel segmentation and classification techniques: intelligent solutions for green computing in medical images, current challenges, open issue... by Abdulsahib A.A., Mahmoud M.A., Mohammed M.A., Rasheed H.H., Mostafa S.A., Maashi M.S.

    Published 2023
    Review
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  14. 14
    Face emotion recognition using artificial intelligence techniques

    Face emotion recognition using artificial intelligence techniques by Kartigayan Muthukaruppan

    Published 2008
    “…In the case of second classification technique, two forms of fuzzy c-mean clustering are considered and their performances are compared. …”
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  15. 15
    2D and 3D video scene text classification

    2D and 3D video scene text classification by Xu, J., Shivakumara, P., Lu, T., Tan, C.L.

    Published 2014
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  16. 16
    Cognitive load assessment through EEG: a dataset from arithmetic and stroop tasks

    Cognitive load assessment through EEG: a dataset from arithmetic and stroop tasks by Nirabi, Ali, Abd Rahman, Faridah, Habaebi, Mohamed Hadi, Sidek, Khairul Azami, Yusoff, Siti Hajar

    Published 2025
    “…This study’s foundation is crucial for advancing stress classification research, with significant implications for cognitive function and well-being.…”
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  17. 17
    Development of drift conversion algorithm for ISFET based pH sensor for continuous measurement system

    Development of drift conversion algorithm for ISFET based pH sensor for continuous measurement system by Othman, Md Rizal, Najib, Muhammad Sharfi, Muda, Razali, Sulaiman, Mohd Herwan, Noordin, Nurul Hazlina, Hadi, Amran Abdul, Kamaludin, Mohamad Yusof, Mohd Ismahad, Syono

    Published 2018
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  18. 18
    Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach

    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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  19. 19
    Pattern Classification of Human Epithelial Images

    Pattern Classification of Human Epithelial Images by Mohd Isa, Mohd Fazlie

    Published 2016
    “…Last but not least, from the mean of properties, it will classify into the pattern after ranging the value of mean properties of each of the pattern itself that has been done in classification stage.…”
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  20. 20
    Small Dataset Learning In Prediction Model Using Box-Whisker Data Transformation

    Small Dataset Learning In Prediction Model Using Box-Whisker Data Transformation by Lateh, Masitah bdul

    Published 2020
    “…There are several data mining tasks such as classification, clustering, prediction, summarization and others. …”
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