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Showing 121 - 140 results of 809 for search '(( elements method algorithm ) OR ((( data using algorithm ) OR ( based existing algorithm ))))', query time: 0.13s Refine Results
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    Using Educational Data Mining Techniques in Predicting Grade-4 students’ performance in TIMSS International Assessments in the UAE by SHWEDEH, FATEN

    Published 2018
    “…Classification is a Data Mining (DM) technique used for prediction. On the other hand, feature selection is the process of finding the best set of features that has the most impact on a specific target. …”
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    Ensemble-Based Spam Detection in Smart Home IoT Devices Time Series Data Using Machine Learning Techniques by Ameema Zainab (16864263)

    Published 2020
    “…The obtained results illustrate the efficacy of the proposed algorithm to analyze the time series data from the IoT devices for spam detection.…”
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    BUC algorithm for iceberg cubes by Nasr, George E.

    Published 2003
    “…The Uniform distribution is used as a basis for comparison. Results show that when the cube is sparse there is a correlation between the data distribution and the running time of the algorithm. …”
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  16. 136

    Nonlinear analysis of shell structures using image processing and machine learning by M.S. Nashed (16392961)

    Published 2023
    “…The proposed approach can be significantly more efficient than training a machine learning algorithm using the raw numerical data. To evaluate the proposed method, two different structures are assessed where the training data is created using nonlinear finite element analysis. …”
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    Use data Mining Techniques to Predict Users’ Engagement on the Social Network Posts in The Period Before, During and After Ramadan by AL RAWASHDEH, HANEEN MOHAMMAD

    Published 2017
    “…Different classification algorithms were applied to the dataset using the Rapidminer tool. …”
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    The use of multi-task learning in cybersecurity applications: a systematic literature review by Shimaa Ibrahim (22155739)

    Published 2024
    “…Five critical applications, such as network intrusion detection and malware detection, were identified, and several tasks used in these applications were observed. Most of the studies used supervised learning algorithms, and there were very limited studies that focused on other types of machine learning. …”