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  1. 1
    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm

    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

    Published 2008
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  2. 2
    A refined classification approach by integrating Landsat Operational Land Imager (OLI) and RADARSAT-2 imagery for land-use and land-cover mapping in a tropical area

    A refined classification approach by integrating Landsat Operational Land Imager (OLI) and RADARSAT-2 imagery for land-use and land-cover mapping in a tropical area by Sameen, Maher Ibrahim, Nahhas, Faten Hamed, Buraihi, Faez Hussein, Pradhan, Biswajeet, Mohamed Shariff, Abdul Rashid

    Published 2016
    “…Different classification algorithms were adopted to classify the integrated Landsat and SAR data, and the maximum likelihood classifier (MLC) was considered the best approach. …”
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  3. 3
    Confidentiality based file attributes and data classification using TsF-KNN

    Confidentiality based file attributes and data classification using TsF-KNN by Ali, M., Jung, L.T.

    Published 2015
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  4. 4
    The Perspective Classification of Balanced Scorecard with Ontology Technique

    The Perspective Classification of Balanced Scorecard with Ontology Technique by Kaewninprasert, Kittisak, Chai-Arayalert, Supaporn, Yamaqupta, Narueban

    Published 2024
    “…The results reveal the accuracy of the proposed ontologies and algorithms on the data from the case study…”
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  5. 5
    Developing an intelligent system to acquire meeting knowledge in problem-based learning environments

    Developing an intelligent system to acquire meeting knowledge in problem-based learning environments by Chiang, A., Baba, M.S.

    Published 2006
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  6. 6
    Modified word representation vector based scalar weight for contextual text classification

    Modified word representation vector based scalar weight for contextual text classification by Abbas Saliimi, Lokman

    Published 2024
    “…For contextual text classification, the pre-trained LLM is further train on classificationspecific labeled data in a process called fine-tuning. …”
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  7. 7
    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.

    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

    Published 2005
    “…Therefore generating a good decision model or classification model is a major component in many data mining researches. …”
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  8. 8
    Efficient feature selection and classification of protein sequence data in bioinformatics

    Efficient feature selection and classification of protein sequence data in bioinformatics by Iqbal, M.J., Faye, I., Samir, B.B., Md Said, A.

    Published 2014
    “…To reduce the gap between newly sequenced protein and proteins with known functions, many computational techniques involving classification and clustering algorithms were proposed in the past. …”
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  9. 9
    Classification Analysis Of The Badminton Five Directional Lunges

    Classification Analysis Of The Badminton Five Directional Lunges by Ho, Zhe Wei

    Published 2018
    “…REP Tree classifier is the best selected classifier for its strength and classification capability. The highest classification accuracy obtained for experimental data-USM and public data-SEA, were 93.75% and 93.01% respectively on REP Tree classifier. …”
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  10. 10
    Predicting game-induced emotions using EEG, data mining and machine learning

    Predicting game-induced emotions using EEG, data mining and machine learning by Min, Xuan Lim, Jason Teo

    Published 2024
    “…Conclusion The fndings in this study fll the existing gap of game-induced emotion recognition feld by providing an in-depth evaluation on the ruleset algorithm’s performance and feasibility of applying the generated rules on the game-induced EEG data for justifying the emotional state prediction result.…”
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  11. 11
    Data-driven state of charge estimation of lithium-ion batteries: Algorithms, implementation factors, limitations and future trends

    Data-driven state of charge estimation of lithium-ion batteries: Algorithms, implementation factors, limitations and future trends by Hossain Lipu M.S., Hannan M.A., Hussain A., Ayob A., Saad M.H.M., Karim T.F., How D.N.T.

    Published 2023
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  12. 12
    An Educational Tool Aimed at Learning Metaheuristics

    An Educational Tool Aimed at Learning Metaheuristics by Kader, Md. Abdul, Jamaluddin, Jamal A., Kamal Z., Zamli

    Published 2020
    “…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
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  13. 13
    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment

    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

    Published 2013
    “…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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  14. 14
    Integrated artificial intelligence-based classification approach for prediction of acute coronary syndrome

    Integrated artificial intelligence-based classification approach for prediction of acute coronary syndrome by Salari, Nader

    Published 2014
    “…The classification performance of K1-K2-NN model was benchmarked against 13 commonly used classification models using repeated random sub-sampling crossvalidation on ACSEKI data set. …”
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  15. 15
    Feature selection for financial data classification: Islamic finance application

    Feature selection for financial data classification: Islamic finance application by Kartiwi, Mira, Gunawan, Teddy Surya, Arundina, Tika, Omar, Mohd. Azmi

    Published 2019
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  16. 16
    Decision tree and rule-based classification for predicting online purchase behavior in Malaysia / Maslina Abdul Aziz, Nurul Ain Mustakim and Shuzlina Abdul Rahman

    Decision tree and rule-based classification for predicting online purchase behavior in Malaysia / Maslina Abdul Aziz, Nurul Ain Mustakim and Shuzlina Abdul Rahman by Abdul Aziz, Maslina, Mustakim, Nurul Ain, Abdul Rahman, Shuzlina

    Published 2024
    “…Therefore, this research tries to fill in some of the gaps by applying decision tree and rule-based algorithms to classify online purchasing behavior amongst Malaysian consumers. …”
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  17. 17
    Backpropagation vs. radial basis function neural model : Rainfall intensity classification for flood prediction using meteorology data

    Backpropagation vs. radial basis function neural model : Rainfall intensity classification for flood prediction using meteorology data by Chai, S.S., Wong, W.K., Goh, K.L.

    Published 2016
    “…The architecture of the neural networks models based on the different combination of inputs and number of hidden neurons to obtain the optimum classification were verified in this study. The influence of the number of training data on the classification results was also analyzed. …”
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  18. 18
    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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  19. 19
    Multi-label risk diabetes complication prediction model using deep neural network with multi-channel weighted dropout

    Multi-label risk diabetes complication prediction model using deep neural network with multi-channel weighted dropout by Dzakiyullah, Nur Rachman

    Published 2025
    “…The early diagnosis of diabetes complications using risk factors remains underexplored, particularly with the application of Multi-Label Classification (MLC). This study addresses this gap by leveraging data from the Behavioral Risk Factor Surveillance System (BRFSS)from 2016 to 2021 to categorize seven diabetes complications simultaneously. …”
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  20. 20
    Development Of Machine Learning User Interface For Pump Diagnostics

    Development Of Machine Learning User Interface For Pump Diagnostics by Lee, Zhao Yang

    Published 2022
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