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  1. 1

    Classification of basal stem rot disease in oil palm using dielectric spectroscopy by Al-Khaled, Al-Fadhl Yahya Khaled

    Published 2018
    “…Without implementing any data reduction algorithm, the highest classification accuracy was found in SVM classifier with 79.55%. …”
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    Thesis
  2. 2

    An intra-severity classification and adaptation technique to improve dysarthric speech recognition accuracy / Bassam Ali Qasem Al-Qatab by Bassam Ali Qasem, Al-Qatab

    Published 2020
    “…The algorithms include Linear Discriminant Analysis (LDA), Artificial Neural Network (ANN), Support Vector Machine (SVM), Naive Bayes (NB), Classification And Regression Tree (CART), Random Forest (RF). …”
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    Thesis
  3. 3

    Mid-infrared spectroscopy for early detection of basal stem rot disease in oil palm by Liaghat, Shohreh, Mansor, Shattri, Ehsani, Reza, Mohd Shafri, Helmi Zulhaidi, Meon, Sariah, Sankaran, Sindhuja

    Published 2014
    “…The selected principal component scores were used in classification using linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), k-nearest neighbor (kNN) and Naive-Bayes (NB) multivariate classification algorithms. …”
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    Article
  4. 4
  5. 5

    Sentiment analysis of customer review for Tina Arena Beauty by Amri, Nur Najwa Shahirah

    Published 2025
    “…Future work may involve expanding the dataset, integrating real-time feedback systems, and evaluating advanced algorithms to improve classification performance further. …”
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    Student Project
  6. 6

    Complexity Analysis of EEG in Patients With Social Anxiety Disorder Using Fuzzy Entropy and Machine Learning Techniques by Al-Ezzi, A., Al-Shargabi, A.A., Al-Shargie, F., Zahary, A.T.

    Published 2022
    “…The main objective of this study is to analyze the electroencephalogram (EEG) complexity of 88 SAD subjects, subdivided into 4 balanced groups (22 severe, 22 moderate, 22 mild, and 22 healthy controls (HCs) using Fuzzy Entropy measure (FE) and machine learning algorithms. …”
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    Article
  7. 7

    Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease by Che Hashim, Izrahayu

    Published 2021
    “…To identify non-infected and BSR-infected trees, the WEKA tool version 3.8.5 was used for classification. The classifiers evaluated in this study were Nave Bayes (NB), Multilayer Perceptron (MLP), and Random Forest (RF). …”
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    Thesis
  8. 8

    An improved hybrid learning approach for better anomaly detection by Mohamed Yassin, Warusia

    Published 2011
    “…Therefore, anomaly detection is often associated with high false alarm with only moderate accuracy of detection rates. In recent years, data mining approach for intrusion detection have been proposed and used such as neural networks, clustering, genetic algorithms, decision trees, and support vector machines. …”
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    Thesis
  9. 9
  10. 10

    Assessment of near-infrared and mid-infrared spectroscopy for early detection of basal stem rot disease in oil palm plantation by Liaghat, Shohreh

    Published 2013
    “…Linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), k-nearest neighbor (kNN), Naïve-Bayes (NB), artificial neural networks (ANNs) and support vector machines (SVMs) classification techniques, were tested to classify the leaf and trunk samples into four levels of disease severity. …”
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    Thesis
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