Search Results - (( model application model algorithm ) OR ( level classification system algorithm ))*

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    Neural network diagnostic system for dengue patients risk classification by Faisal, T., Taib, M.N., Ibrahim, Fatimah

    Published 2012
    “…However, it has been a great challenge for the physicians to identify the level of risk in dengue patients due to overlapping of the medical classification criteria. …”
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    Article
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    Imbalanced Classification Methods for Student Grade Prediction: A Systematic Literature Review by Abdul Bujang S.D., Selamat A., Krejcar O., Mohamed F., Cheng L.K., Chiu P.C., Fujita H.

    Published 2024
    “…The study also presents the most common balancing methods published from 2015 to 2021 and highlights their impact on resolving imbalanced classification in three approaches: data-level, algorithm-level, and hybrid-level. …”
    Review
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    Classification of Citrus (Rutaceae) by Using Image Processing by Najwa Bari'ah Mohd Tabri

    Published 2019
    “…This research will be conducted by using digital image processing approach based on the morphological features of leaf with the combination of gray level co-occurrence matrix (GLCM), Prewitt and Canny algorithm and training classification models by using support vector machine (SVM). …”
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    Undergraduate Final Project Report
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    Imbalanced Classification Methods for Student Grade Prediction : A Systematic Literature Review by Siti Dianah, Abdul Bujang, Ali, Selamat, Ondrej, Krejcar, Farhana, Mohamed, Cheng, Lim Kok, Chiu, Po Chan, Hamido, Fujita

    Published 2023
    “…The study also presents the most common balancing methods published from 2015 to 2021 and highlights their impact on resolving imbalanced classification in three approaches: data-level, algorithm-level, and hybrid-level. …”
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    Article
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    Semantic-k-NN algorithm: An enhanced version of traditional k-NN algorithm by Ali, M., Jung, L.T., Abdel-Aty, A.-H., Abubakar, M.Y., Elhoseny, M., Ali, I.

    Published 2020
    “…The k-NN algorithm is one of the most renowned ML algorithms widely used in the area of data classification research. …”
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    Article
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    Semantic-k-NN algorithm: An enhanced version of traditional k-NN algorithm by Ali, M., Jung, L.T., Abdel-Aty, A.-H., Abubakar, M.Y., Elhoseny, M., Ali, I.

    Published 2020
    “…The k-NN algorithm is one of the most renowned ML algorithms widely used in the area of data classification research. …”
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    Article
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    Power quality problem classification based on Wavelet Transform and a Rule-Based method by Nallagownden, Perumal

    Published 2010
    “…These features and together with the duration of disturbance of occurrence obtained from 1st level of detail, they form the criteria for a Rule-Based software algorithm for detecting different kinds of power quality disturbances effectively. …”
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    Conference or Workshop Item
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    Identification Of Flow Blockage Levels In Centrifugal Pump By Machine Learning by Ng, Woon Li

    Published 2021
    “…Machine learning can be used as a preventive measure to detect the blockage in the pump inlet at inception level. The purpose of this research is to develop an effective machine learning model for the classification of flow blockage levels in the centrifugal pump by using the statistically significant features from vibration and acoustic analysis. …”
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    Monograph
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    Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification by Mohammed, Alhassan Afnan

    Published 2022
    “…Deep Belief Network (DBN) is a sophisticated learning system that requires a high level of approach and executes well. …”
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    Thesis
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    Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…However, the learning complexity of classification is increased due to the expansion number of learning model. Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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    Thesis
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    Power Quality Problem Classification Based on Wavelet Transform and a Rule-Based method by Chuah , Heng keow, Nallagownden, Perumal, Kondapalli, K.S. Rama Rao

    Published 2010
    “…These features and together with the duration of disturbance of occurrence obtained from 1st level of detail, they form the criteria for a Rule-Based software algorithm for detecting different kinds of power quality disturbances effectively. …”
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    Conference or Workshop Item
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    Power Quality Problem Classification Based on Wavelet Transform and a Rule-Based method by keow, Chuah Heng, Nallagownden, Perumal, K. S. , Rama Rao

    Published 2010
    “…These features and together with the duration of disturbance of occurrence obtained from 1st level of detail, they form the criteria for a Rule-Based software algorithm for detecting different kinds of power quality disturbances effectively. …”
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    Conference or Workshop Item
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    Development of interactive application for classification of Artocarpus Species by Abdul Ghapar, Nadia

    Published 2020
    “…Support Vector Machine (SVM) will be used to get the highest accuracy for the classification of Artocarpus species. The combination of Prewitt algorithm, Canny alogorithm, Gray-Level co-occurrence matrix will be used in SVM. …”
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    Undergraduate Final Project Report
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    Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying by Khaw , Hui Ying

    Published 2019
    “…An ensemble of these algorithms is an intelligent and adaptive solution, producing a clean output, while preserving significant pixel information. …”
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    Thesis
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    Classification of EEG spectrogram image with ANN approach for brainwave balancing application by Mahfuzah, Mustafa, Mohd Nasir, Taib, Zunairah, Murat, Norizam, Sulaiman, Siti Armiza, Mohd Aris

    Published 2011
    “…The result shows that the proposed model is able to classify EEG spectrogram images with 77% to 84% accuracy for three classes of brainwave balancing application with an optimized ANN model in training by varying the neurons in the hidden layer, epoch, momentum rate and learning rate.…”
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    Article