Search Results - (( framework implementation using algorithm ) OR ( data classification using algorithm ))

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  1. 1

    An enhanced classification framework for intrusions detection system using intelligent exoplanet atmospheric retrieval algorithm by Slamet, ., Izzeldin Ibrahim, Mohamed Abdelaziz

    Published 2022
    “…Currently, many companies use data mining for various implementations. One form of implementation is intrusion detection system (IDS). …”
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    Article
  2. 2

    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

    Published 2019
    “…The proposed algorithm is compared with the state-of-the-art feature selection algorithms using three different datasets. …”
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    Thesis
  3. 3

    Genetic algorithm based ensemble framework for sentiment analysis by Lai, Po Hung

    Published 2018
    “…Machine Learning classification is commonly used in sentiment analysis and it requires plain text documents to be transformed to analyzable data through feature extraction and selection. …”
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    Thesis
  4. 4

    An enhanced classification framework for intrusions detection system using intelligent exoplanet atmospheric retrieval by Slamet, Slamet, Izzeldin, Ibrahim Mohamed Abdelaziz

    Published 2022
    “…Currently, many companies use data mining for various implementations. One form of implementation is intrusion detection system (IDS). …”
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    Article
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    A COLLABORATIVE FRAMEWORK FOR ANDROID MALWARE IDENTIFICATION USING DYNAMIC ANALYSIS by Thayaaleni, Rajandran

    Published 2019
    “…The scope of this project focuses on Android Malware detection by using dynamic analysis. The methods to implement this project is through data collection, feature extraction, feature selection, and classification process. …”
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    Final Year Project Report / IMRAD
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    A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition by Babiker, Elsadig Ahmed Mohamed

    Published 2002
    “…Classification rules were generated from training feature vectors set, and a modified form of the standard voter classification algorithm, that use the rough sets generated rules, was applied. …”
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    Thesis
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    Affect classification using genetic-optimized ensembles of fuzzy ARTMAPs by Liew, W.S., Seera, M., Loo, C.K., Lim, E.

    Published 2015
    “…Speciation was implemented using subset selection of classification data attributes, as well as using an island model genetic algorithms method. …”
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    Article
  10. 10

    Edge assisted crime prediction and evaluation framework for machine learning algorithms by Adhikary, Apurba, Murad, Saydul Akbar, Munir, Md Shirajum, Choong Seon, Hong Seong

    Published 2022
    “…Criminal risk is predicted using classification models for a particular time interval and place. …”
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    Conference or Workshop Item
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    A novel framework for potato leaf disease detection using an efficient deep learning model by Mahum, R., Munir, H., Mughal, Z.-U.-N., Awais, M., Sher Khan, F., Saqlain, M., Mahamad, S., Tlili, I.

    Published 2022
    “…Moreover, the usage of the reweighted cross-entropy loss function makes our proposed algorithm more robust as the training data is highly imbalanced. …”
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    Article
  12. 12

    A novel framework for potato leaf disease detection using an efficient deep learning model by Mahum, R., Munir, H., Mughal, Z.-U.-N., Awais, M., Sher Khan, F., Saqlain, M., Mahamad, S., Tlili, I.

    Published 2022
    “…Moreover, the usage of the reweighted cross-entropy loss function makes our proposed algorithm more robust as the training data is highly imbalanced. …”
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    Article
  13. 13

    Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data by Qadir Saraf, Tara Othman, Fuad, Norfaiza, Md Taujuddin, Nik Shahidah Afifi

    Published 2023
    “…Meta-heuristic searching with embedding information theory-based criteria in the fitness function for selecting the relevant features is used widely in current feature selection algorithms. …”
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    Article
  14. 14

    Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data by Qadir Saraf, Tara Othman, Fuad, Norfaiza, Md Taujuddin, Nik Shahidah Afifi

    Published 2023
    “…Meta-heuristic searching with embedding information theory-based criteria in the fitness function for selecting the relevant features is used widely in current feature selection algorithms. …”
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    Article
  15. 15

    Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data by Qadir Sara, Tara Othman, Fuad, Norfaiza, Md Taujuddin, Nik Shahidah Afifi

    Published 2023
    “…Meta-heuristic searching with embedding information theory-based criteria in the fitness function for selecting the relevant features is used widely in current feature selection algorithms. …”
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    Article
  16. 16

    A framework for malware identification based on behavior by Mohamad Fadli, Zolkipli

    Published 2012
    “…The IF-THEN Prediction Rules which is generated using the data mining technique, ID3 Algorithm is used. …”
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    Thesis
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    An Improved Diabetes Risk Prediction Framework : An Indonesian Case Study by Sutanto, Daniel Hartono

    Published 2018
    “…Pre-processing resolves the issue of missing data and hence normalizes the data.Outlier treatment employs k-mean clustering to validate the class.Suitable components were selected through comparison of classifier algorithms and feature selection.Attribute weighting based feature selection was selected for assigning weightage.Weighted risk factor was used on training dataset in order to improve accuracy and computation time of the prediction. …”
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    Thesis
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    Poverty risk prediction based on socioeconomic factors using machine learning approach by Mohd Zawari, Nur Farhana Adibah

    Published 2025
    “…Information gain was used in the feature selection and four classification algorithms namely, Logistic Regression, Random Forest, Decision Tree, and Gradient Boosted, were implemented and tested with the incorporation of 10-fold cross-validation and splitting 70:30 in WEKA. …”
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    Student Project
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