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  1. 1
    Enhanced mechanism to handle missing data of Hadith classifier

    Enhanced mechanism to handle missing data of Hadith classifier by Aldhlan, Kawther A., Zeki, Ahmed M., Zeki, Akram M.

    Published 2011
    “…Decision tree algorithms have the ability to deal with missing values or wrong data. …”
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  2. 2
    Crown counting and mapping of missing oil palm tree using airborne imaging system

    Crown counting and mapping of missing oil palm tree using airborne imaging system by Kee, Ya Wern

    Published 2019
    “…Watershed segmentation function was employed to separate the connected trees and missing trees regions. Different structuring elements of morphological filtering were applied to oil palm trees and missing trees counting for the purpose of noise removal. …”
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  3. 3
    Improving knowledge extraction of Hadith classifier using decision tree algorithm

    Improving knowledge extraction of Hadith classifier using decision tree algorithm by Aldhaln, Kawther, Zeki, Akram M., Zeki, Ahmed M., Alreshidi, Hamad

    Published 2012
    “…Decision tree algorithms have the ability to deal with missing values. …”
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  4. 4
    ExtraImpute: a novel machine learning method for missing data imputation

    ExtraImpute: a novel machine learning method for missing data imputation by Alabadla, Mustafa, Sidi, Fatimah, Ishak, Iskandar, Ibrahim, Hamidah, Affendey, Lilly Suriani, Hamdan, Hazlina

    Published 2022
    “…In this paper, we propose a new imputation approach using Extremely Randomized Trees (Extra Trees) of machine learning ensemble learning methods named (ExtraImpute) to tackle numerical missing values in healthcare context. …”
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  5. 5
    Performance analysis of machine learning algorithms for missing value imputation

    Performance analysis of machine learning algorithms for missing value imputation by Ismail, Amelia Ritahani, Zainal Abidin, Nadzurah, Emran, Nurul Akmar

    Published 2018
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  6. 6
    Performance analysis of machine learning algorithms for missing value imputation

    Performance analysis of machine learning algorithms for missing value imputation by Zainal Abidin, Nadzurah, Ismail, Amelia Ritahani, Emran, Nurul Akmar

    Published 2018
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  7. 7
    Intelligent imputation method for mix data-type missing values to improve data quality

    Intelligent imputation method for mix data-type missing values to improve data quality by Alabadla, Mustafa R. A.

    Published 2024
    “…Missing data is a widespread data quality issue across various domains. …”
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  8. 8
    New Learning Models for Generating Classification Rules Based on Rough Set Approach

    New Learning Models for Generating Classification Rules Based on Rough Set Approach by Al Shalabi, Luai Abdel Lateef

    Published 2000
    “…Recently, different models were used to generate knowledge from vague and uncertain data sets such as induction decision tree, neural network, fuzzy logic, genetic algorithm, rough set theory, and others. …”
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  9. 9
    Tangible interaction learning model to enhance learning activity processes among children with dyslexia

    Tangible interaction learning model to enhance learning activity processes among children with dyslexia by Jamalai@Jamali, Siti Nurliana

    Published 2024
    “…Missing data is a widespread data quality issue across various domains. …”
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  10. 10
    Detecting Remote-To-Local (R2L) attack using Decision Tree algorithm / Ahmad Nasreen Aqmal Mohd Nordin

    Detecting Remote-To-Local (R2L) attack using Decision Tree algorithm / Ahmad Nasreen Aqmal Mohd Nordin by Mohd Nordin, Ahmad Nasreen Aqmal

    Published 2024
    “…The implementation phase focuses on the deployment of the Decision Tree algorithm and system evaluation through functionality testing. …”
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  11. 11
    A novel approach for handling missing data to enhance network intrusion detection system

    A novel approach for handling missing data to enhance network intrusion detection system by Tahir, Mahjabeen, Abdullah, Azizol, Udzir, Nur Izura, Kasmiran, Khairul Azhar

    Published 2025
    “…Our approach employs the Random Missing Value (RMV) algorithm to simulate missing data, enabling thorough testing and comparison of various imputation techniques. …”
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  12. 12
    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection

    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

    Published 2022
    “…The simulation is implemented with iFogSim and java programming language. …”
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  13. 13
    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing

    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

    Published 2011
    “…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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  14. 14
    Ant colony optimization algorithm for load balancing in grid computing

    Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2012
    “…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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  15. 15
    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
    “…Keyword: Random Forest, Bayesian Inference, Classification, Regression, Missing Data.…”
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  16. 16
    OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT

    OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

    Published 2023
    “…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”
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  17. 17
    Data Mining Analysis Of Chronic Kidney Disease (CKD) Level

    Data Mining Analysis Of Chronic Kidney Disease (CKD) Level by Mohd Harizi, Muhammad Hafizam Afiq

    Published 2022
    “…Data classifications are performed at a 10-fold-cross-validation mode using Naïve Bayes (NB), Support Vector Machine (SVM), and J48 Trees. …”
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  18. 18
    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization

    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    Published 2019
    “…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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  19. 19
    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
    “…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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  20. 20
    Optimizing the light gradient-boosting machine algorithm for an efficient early detection of coronary heart disease

    Optimizing the light gradient-boosting machine algorithm for an efficient early detection of coronary heart disease by Temidayo Oluwatosin Omotehinwa, David Opeoluwa Oyewola, Ervin Gubin Moung

    Published 2024
    “…The study's strengths include its comprehensive approach to addressing missing data and class imbalance and the fine-tuning of hyperparameters through Bayesian Optimization. …”
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