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  1. 1
    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
    “…Missing values lead to the difficulty of extracting useful information from that data set. …”
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  2. 2
    An Apriori-based Data Analysis on Suspicious Network Event Recognition

    An Apriori-based Data Analysis on Suspicious Network Event Recognition by Jian, Z., Sakai, H., Watada, J., Roy, A., Hassan, M.H.B.

    Published 2019
    “…Then, each missing value in the test data set is decided by using the obtained rules. …”
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  3. 3
    Image clustering comparison of two color segmentation techniques

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…Finally, the algorithm found, which would solve the image segmentation problem.…”
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  4. 4
    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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  5. 5
    An enhanced robust association rules method for missing values imputation in Arabic language data set

    An enhanced robust association rules method for missing values imputation in Arabic language data set by Salem, Awsan Thabet

    Published 2023
    “…In this thesis, the Enhanced Robust Association Rules (ERAR) method for missing values imputation is proposed. …”
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  6. 6
    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
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  7. 7
    NIS-Apriori-based rule generation with three-way decisions and its application system in SQL

    NIS-Apriori-based rule generation with three-way decisions and its application system in SQL by Sakai, H., Nakata, M., Watada, J.

    Published 2020
    “…One of the topics that are considered is the possibility of estimating missing values via the obtained certain rules. The proposed methodology and the environment yielded by NIS-Apriori-based rule generation in SQL are useful for table data analysis with three-way decisions. …”
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  8. 8
    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
    “…The extraction of minimum rules operation is conducted after the default rules have been generated in order to obtain the most useful discovered rules. …”
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  9. 9
    Fuzzy modeling using Bat Algorithm optimization for classification

    Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

    Published 2018
    “…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. The value of parameter is already set to use when applying every dataset in an experiment. …”
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  10. 10
    Deep-learning-based detection of missing road lane markings using YOLOv5 algorithm

    Deep-learning-based detection of missing road lane markings using YOLOv5 algorithm by Sophian, Ali, Azmi, Nur Hanisah, Bawono, Ali Aryo

    Published 2021
    “…This road lane markings mainly used to provide guidance and information for road user to comply with the rule of the road. …”
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  11. 11
    Automatic Number Plate Recognition on android platform: With some Java code excerpts

    Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

    Published 2016
    “…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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  12. 12
    Exploratory analysis with association rule mining algorithms in the retail industry / Alaa Amin Hashad ... [et al.]

    Exploratory analysis with association rule mining algorithms in the retail industry / Alaa Amin Hashad ... [et al.] by Hashad, Alaa Amin, Khaw, Khai Wah, Alnoor, Alhamzah, Chew, Xin Ying

    Published 2024
    “…The FP-Growth algorithm was found to be faster and more effective than the Apriori algorithm in extracting frequent item sets and generating association rules. …”
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  13. 13
    Development of seven segment display recognition using TensorFlow on Raspberry Pi

    Development of seven segment display recognition using TensorFlow on Raspberry Pi by Gunawan, Teddy Surya, Mohammad Reduwan, Haque, Yaacob, Mashkuri, Mohamed Azmin, Nor Fadhillah, Ismail, Nanang, Ismail, Md Yusof, Kartiwi, Mira, A. Rahman, Azhar

    Published 2022
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  14. 14
    Breast cancer detection by using associative classifier with rule refinement method based on relevance feedback

    Breast cancer detection by using associative classifier with rule refinement method based on relevance feedback by Abubacker, Nirase Fathima, Azman, Azreen, Doraisamy, Shyamala, Azmi Murad, Masrah Azrifah

    Published 2022
    “…This paper aims to address this issue by refining rules that are static using dynamic rule refinement technique. …”
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  15. 15
    Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor

    Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor by Adilah, Abdul Ghapor

    Published 2017
    “…As for the multiple outliers, a clustering algorithm is considered and a dendogram to visualise the clustering algorithm is used. …”
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  16. 16
    Development of intelligent hybrid learning system using clustering and knowledge-based neural networks for economic forecasting : First phase

    Development of intelligent hybrid learning system using clustering and knowledge-based neural networks for economic forecasting : First phase by Che Mat @ Mohd Shukor, Zamzarina, Md Sap, Mohd Noor

    Published 2004
    “…We proposed KMeans clustering algorithm that is based on multidimensional scaling, joined with neural knowledge based technique algorithm for supporting the learning module to generate interesting clusters that will generate interesting rules for extracting knowledge from stock exchange databases efficiently and accurately.…”
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  17. 17
    Minimizing Scheduling Overhead In LRE-TL Real-Time Multiprocessor Scheduling Algorithm

    Minimizing Scheduling Overhead In LRE-TL Real-Time Multiprocessor Scheduling Algorithm by Alhussian, Hitham, Zakaria, Nordin, Hussin, Fawnizu Azmadi

    Published 2015
    “…LRE-TL achieves optimality by employing the fairness rule at the end of each time slice in a fluid schedule model. …”
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  18. 18
    Privacy optimization and intrusion detection in modbus/tcp network-based scada in water distribution systems

    Privacy optimization and intrusion detection in modbus/tcp network-based scada in water distribution systems by Franco, Daniel Jose Da Graca Peceguina

    Published 2021
    “…Another problematic aspect is related to the intrusion detection solutions that are based on machine learning cluster algorithms to learn systems’ specifications and extract general state-based rules for attacks identification. …”
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  19. 19
    Minimizing scheduling overhead in LRE-TL real-time multiprocessor scheduling algorithm

    Minimizing scheduling overhead in LRE-TL real-time multiprocessor scheduling algorithm by Alhussian, H.S.A., Zakaria, M.N.B., Hussin, F.A.B.

    Published 2017
    “…LRE-TL achieves optimality by employing the fairness rule at the end of each time slice in a uid schedule model. …”
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  20. 20
    Improving performance of automated coronary arterial tree center-line extraction, stent localization and tracking

    Improving performance of automated coronary arterial tree center-line extraction, stent localization and tracking by Boroujeni, Farsad Zamani

    Published 2012
    “…The first contribution is automatic detection of seed points which serve as a prerequisite step for centerline extraction algorithm. The solution consists of an algorithm for automatic collection of candidate seed points using efficient grid line searching mechanism and a validation method which uses local geometric and intensity based features as effective validation rules to discriminate between the actual seed point and false alarms. …”
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