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  1. 1
    Breast cancer disease classification using fuzzy-ID3 algorithm with FUZZYDBD method: automatic fuzzy database definition

    Breast cancer disease classification using fuzzy-ID3 algorithm with FUZZYDBD method: automatic fuzzy database definition by Nur Farahaina, Idris, Mohd Arfian, Ismail

    Published 2021
    “…This paper proposed the fuzzy-ID3 (FID3) algorithm, a fuzzy decision tree as the classification method in breast cancer detection. …”
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  2. 2
    Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak

    Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

    Published 2019
    “…The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. …”
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    Thesis
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  3. 3
    An analysis of intrusion detection classification using supervised machine learning algorithms on NSL-KDD dataset / Sarthak Rastogi ... [et al.]

    An analysis of intrusion detection classification using supervised machine learning algorithms on NSL-KDD dataset / Sarthak Rastogi ... [et al.] by Rastogi, Sarthak, Shrotriya, Archit, Singh, Mitul Kumar, Potukuchi, Raghu Vamsi

    Published 2022
    “…To this end, this paper studies the classification analysis of intrusion detection using various supervised learning algorithms such as SVM, Naive Bayes, KNN, Random Forest, Logistic Regression and Decision tree on the NSL-KDD dataset. …”
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  4. 4
    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
    “…These refined rules are used for classification of future test examples that leads to improved prediction accuracy in comparison with the classifier that uses generalized static rules. …”
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  5. 5
    Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization

    Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

    Published 2014
    “…This paper presents a classification of android malware using candidate detectors generated from an unsupervised association rule of Apriori algorithm improved with particle swarm optimization to train three different supervised classifiers. …”
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  6. 6
    Compressing and improving fuzzy rules using genetic algorithm and its application to fault detection

    Compressing and improving fuzzy rules using genetic algorithm and its application to fault detection by Yap K.S., Wong S.Y., Tiong S.K.

    Published 2023
    Conference Paper
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  7. 7
    Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization

    Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

    Published 2015
    “…However, supervised learning technique has limitations for malware classification task. This paper presents a classification approach on android malware using candidate detectors generated from an unsupervised association rule of Apriori Algorithm. …”
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  8. 8
    An improved method using fuzzy system based on hybrid boahs for phishing attack detection

    An improved method using fuzzy system based on hybrid boahs for phishing attack detection by Noor Syahirah, Nordin

    Published 2022
    “…The experiment was executed by using k-fold cross validation techniques for predicting the classification algorithm performance. …”
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  9. 9
    Optimizing the performance of mobile malware detection using the indexing rule

    Optimizing the performance of mobile malware detection using the indexing rule by Ahmad I.N., Farida Hazwani Mohd Ridzuan, Madihah Mohd Saudi

    Published 2024
    journal::journal article
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  10. 10
    An ensemble learning method for spam email detection system based on metaheuristic algorithms

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…A well known task is classification that predicts the class of new instances using known features or attributes automatically. …”
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  11. 11
    Power quality problem classification based on Wavelet Transform and a Rule-Based method

    Power quality problem classification based on Wavelet Transform and a Rule-Based method by Nallagownden, Perumal

    Published 2010
    “…This paper describes a Wavelet Transform and Rule-Based method for detection and classification of various events of power quality disturbances. …”
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  12. 12
    Power Quality Problem Classification Based on Wavelet Transform and a Rule-Based method

    Power Quality Problem Classification Based on Wavelet Transform and a Rule-Based method by Chuah , Heng keow, Nallagownden, Perumal, Kondapalli, K.S. Rama Rao

    Published 2010
    “…This paper describes a Wavelet Transform and Rule-Based method for detection and classification of various events of power quality disturbances. …”
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  13. 13
    Power Quality Problem Classification Based on Wavelet Transform and a Rule-Based method

    Power Quality Problem Classification Based on Wavelet Transform and a Rule-Based method by keow, Chuah Heng, Nallagownden, Perumal, K. S. , Rama Rao

    Published 2010
    “…This paper describes a Wavelet Transform and Rule-Based method for detection and classification of various events of power quality disturbances. …”
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  14. 14
    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad

    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

    Published 2018
    “…Experimental results show that the developed methods and model are able to classify the Harumanis quality with accuracy of 79% using fuzzy classification based on shape and size.…”
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  15. 15
    Winsorize tree algorithm for handling outliers in classification problem

    Winsorize tree algorithm for handling outliers in classification problem by Ch’ng, Chee Keong

    Published 2016
    “…This study uses three stopping rules: node achieved the minimum 10% of total training set,…”
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  16. 16
    Android malware detection using PMCC heatmap and Fuzzy Unordered Rule Induction Algorithm (FURIA)

    Android malware detection using PMCC heatmap and Fuzzy Unordered Rule Induction Algorithm (FURIA) by Nur Khairani, Kamarudin, Ahmad Firdaus, Zainal Abidin, Azlee, Zabidi, Ferda, Ernawan, Syifak, Izhar Hisham, Mohd Faizal, Ab Razak

    Published 2023
    “…For machine learning classification algorithms, we used a type of fuzzy logic called lattice reasoning. …”
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  17. 17
    Classification of credit card holder behavior using K Nearest Neighbor algorithm / Ahmad Faris Rahimi

    Classification of credit card holder behavior using K Nearest Neighbor algorithm / Ahmad Faris Rahimi by Rahimi, Ahmad Faris

    Published 2017
    “…The more the algorithm use in a project the better performance will be in result.…”
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  18. 18
    Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool

    Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool by Nurshafiqa Saffah, Mohd Sharif

    Published 2018
    “…From the data analysis using WEKA software, the production rules classifier (PART) is found to be the most accurate classification algorithm in classifying the emotion which yields the highest precision percentage of 99.6% compared to J48 (99.5%) and Naïve Bayes (96.2%). …”
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  19. 19
    Optimized techniques for landslide detection and characteristics using LiDAR data

    Optimized techniques for landslide detection and characteristics using LiDAR data by Mezaal, Mustafa Ridha

    Published 2018
    “…The locations of landslides were detected accurately by employing two Machine learning classifiers, namely, SVM and RF, decision rule and hierarchal rules sets were developed by applying decision tree (DT) algorithm to provide improved landslide inventory. …”
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  20. 20
    POWER QUALITY CLASSIFICATION WITH DE-NOISING SCHEME USING WAVELET TRANSFORM AND RULE- BASED METHOD

    POWER QUALITY CLASSIFICATION WITH DE-NOISING SCHEME USING WAVELET TRANSFORM AND RULE- BASED METHOD by HENG KEOW, CHUAH

    Published 2012
    “…This thesis focuses on a Rule-Based method based on wavelet transform to detect and classify various events of power quality disturbances. …”
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