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  1. 1
    Detection and classification of conflict flows in SDN using machine learning algorithms

    Detection and classification of conflict flows in SDN using machine learning algorithms by Mutaz Hamed Hussien Khairi, Sharifah Hafizah Syed Ariffin, Nurul Mu'azzah Abdul Latiff, Kamaludin Mohamad Yusof, Mohamed Khalafalla Hassan, Fahad Taha Al-Dhief, Mosab Hamda, Suleman Khan, Muzaffar Hamzah

    Published 2021
    “…Moreover, applying machine learning algorithms in the identification and classification of conflicting flows has limitations. …”
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  2. 2
    The impact of fuzzy discretization�s output on classification accuracy of random forest classifier

    The impact of fuzzy discretization�s output on classification accuracy of random forest classifier by Fikri, M.N., Hassan, M.F., Tran, D.C.

    Published 2020
    “…Random Forest is known as among the widely used classification algorithms by researchers and machine learning enthusiast in solving classification problems. …”
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  3. 3
    Framework for mining XML format business process log data

    Framework for mining XML format business process log data by Ang, Jin Sheng

    Published 2024
    “…The Random Forest model outperformed others with a classification accuracy of 0.75 for simulation data, while the decision tree achieved the highest accuracy (0.7474) in the BPIC 2017 dataset. …”
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  4. 4
    A class skew-insensitive ACO-based decision tree algorithm for imbalanced data sets

    A class skew-insensitive ACO-based decision tree algorithm for imbalanced data sets by Mohd Razali, Muhamad Hasbullah, Saian, Rizauddin, Yap, Bee Wah, Ku-Mahamud, Ku Ruhana

    Published 2021
    “…This study proposed an enhanced algorithm called hellingerant-tree-miner (HATM) which is inspired by ant colony optimization (ACO) metaheuristic for imbalanced learning using decision tree classification algorithm. …”
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  5. 5
    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly

    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

    Published 2019
    “…Even a normal people using clustering to grouping their data. …”
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  6. 6
    Modelling of the anti-collision algorithm in RFID system: article / Shafinaz Ismail

    Modelling of the anti-collision algorithm in RFID system: article / Shafinaz Ismail by Ismail, Shafinaz

    Published 2014
    “…To avoid these collisions, there are several anti-collision algorithms used in the RFID system. The major classifications of the algorithms are Aloha based protocols and tree based protocols. …”
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  7. 7
    Modelling of the anti-collision algorithm in RFID system / Shafinaz Ismail

    Modelling of the anti-collision algorithm in RFID system / Shafinaz Ismail by Ismail, Shafinaz

    Published 2014
    “…To avoid these collisions, there are several anti-collision algorithms used in the RFID system. The major classifications of the algorithms are Aloha based protocols and tree based protocols. …”
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  8. 8
    Algorithm comparison for data mining classification: assessing bank customer credit scoring default risk

    Algorithm comparison for data mining classification: assessing bank customer credit scoring default risk by Elaf Adel Abbas, Nisreen Abbas Hussein

    Published 2024
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  9. 9
    Fatigue State Detection Through Multiple Machine Learning Classifiers Using EEG Signal

    Fatigue State Detection Through Multiple Machine Learning Classifiers Using EEG Signal by Hasan, Md Mahmudul, Hossain, Mirza Mahfuj, Norizam, Sulaiman

    Published 2023
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  10. 10
    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
    “…Four conventional classification algorithms: naïve bayes (NB), support vector machines (SVM), nearest neighbor (k-NN), and decision trees (J48) classifiers are implemented in identifying and categorizing tweet data of three political figures in Malaysia: Dato Seri Anwar, Dato Hadi Awang, and Lim Guang Eng, as either positive, negative, or neutral perceptions. …”
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  11. 11
    A corrosion prediction model for oil and gas pipeline using CMARPGA

    A corrosion prediction model for oil and gas pipeline using CMARPGA by Chern-Tong, H., Aziz, I.B.A.

    Published 2016
    “…This proposed prediction model named CMARGA is then enhanced by using genetic algorithm in order build an optimum decision tree. …”
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  12. 12
    Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data

    Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data by Oyebayo, Olaniran Ridwan

    Published 2018
    “…Performance analysis was achieved using simulated and eighteen real-life classification and regression microarray cancer datasets. …”
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  13. 13
    SANAsms: Secure short messaging system for secure GSM mobile communication

    SANAsms: Secure short messaging system for secure GSM mobile communication by Anuar, N.B., Azlan, I.M., Wahid, A.W.A., Zakaria, O.

    Published 2008
    “…The system is developed using Java 2 Micro Edition (J2ME) which is written in Java. …”
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  14. 14
    Diabetes Diagnosis And Level Of Care Fuzzy Rule-Based Model Utilizing Supervised Machine Learning For Classification And Prediction

    Diabetes Diagnosis And Level Of Care Fuzzy Rule-Based Model Utilizing Supervised Machine Learning For Classification And Prediction by Mohd Aris, Teh Noranis, Abu Bakar, Azuraliza, Mahiddin, Normadiah, Zolkepli, Maslina

    Published 2024
    “…In this study, ten supervised machine learning algorithms namely the J48, Logistic, NaiveBayes Updateable, RandomTree, BayesNet, AdaBoostM1, Random Forest, Multilayer Perceptron, Bagging and Stacking are applied for a simulated diabetes fuzzy dataset, verified by medical experts. …”
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  15. 15
    Cyberbullying detection: a machine learning approach

    Cyberbullying detection: a machine learning approach by Yeong, Su Yen

    Published 2022
    “…The machine learning algorithm, Support Vector Machine was chosen after comparing it with other algorithms such as Multinomial Naïve Bayes, Decision Tree Classifier, and Random Forest Classifier. …”
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  16. 16
    Water Quality Index Classification of Southeast, South and West Asia Rivers using Machine Learning Algorithms

    Water Quality Index Classification of Southeast, South and West Asia Rivers using Machine Learning Algorithms by Shaheed H., Zawawi M.H., Hayder G.

    Published 2025
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  17. 17
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Electing the best set of features will help to improve the classifier predictions in terms of the normal and abnormal pattern. The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. …”
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  18. 18
    Challenges of hidden data in the unused area two within executable files

    Challenges of hidden data in the unused area two within executable files by Naji, Ahmed Wathik, Zaidan, A.A., Zaidan, B.B.

    Published 2009
    “…The designed algorithms were intended to help in proposed system aim to hide and retract information (data file) with in unused area 2 of any execution file(exe.file). …”
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  19. 19
    Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions

    Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions by Saraswati, Galuh Wilujeng

    Published 2017
    “…Two sets of experimental data involving 20 diabetic patients and 20 healthy subjects were collected from CITO laboratory Semarang Central Java, Indonesia. …”
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