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  1. 1
    Outlier Detection Technique in Data Mining: A Research Perspective

    Outlier Detection Technique in Data Mining: A Research Perspective by Mansur, M. O., Md. Sap, Mohd. Noor

    Published 2005
    “…Finding ,removing and detecting outliers is very important in data mining, for example error in large databases can be extremely common, so an important property of a data mining algorithm is robustness with respect to outliers in the database. …”
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  2. 2
    Parallel distributed genetic algorithm development based on microcontrollers framework

    Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

    Published 2023
    Conference paper
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  3. 3
    Designing a new model to detect Trojan Horse based on knowledge discovery and data mining

    Designing a new model to detect Trojan Horse based on knowledge discovery and data mining by Areej Mustafa Khlaif Abuzaid

    Published 2024
    thesis::master thesis
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  4. 4
    Dissimilarity algorithm on conceptual graphs to mine text outliers

    Dissimilarity algorithm on conceptual graphs to mine text outliers by Kamaruddin, Siti Sakira, Hamdan, Abdul Razak, Abu Bakar, Azuraliza, Mat Nor, Fauzias

    Published 2009
    “…In Comparison to other text outlier detection method, this approach managed to capture the semantics of documents through the use of CGs and is convenient to detect outliers through a simple dissimilarity function.Furthermore, our proposed algorithm retains a linear complexity with the increasing number of CGs.…”
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  5. 5
    Sentiment mining in twitter for early depression detection / Najihah Salsabila Ishak

    Sentiment mining in twitter for early depression detection / Najihah Salsabila Ishak by Ishak, Najihah Salsabila

    Published 2021
    “…A comparison between built-in Scikit Learn Naive Bayes algorithm, and the scratch Naive Bayes algorithm is used to measure its effectiveness in terms of accuracy. …”
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    Thesis
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  6. 6
    Unsupervised Anomaly Detection with Unlabeled Data Using Clustering

    Unsupervised Anomaly Detection with Unlabeled Data Using Clustering by Chimphlee, Witcha, Abdullah, Abdul Hanan, Md. Sap, Mohd. Noor

    Published 2005
    “…We present a clustering-based intrusion detection algorithm, unsupervised anomaly detection, which trains on unlabeled data in order to detect new intrusions. …”
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  7. 7
    Improving intrusion detection using genetic algorithm

    Improving intrusion detection using genetic algorithm by Hashemi, V. Moraveji, Muda, Zaiton, Yassin, Warusia

    Published 2013
    “…The validity of this approach is verified using Knowledge Discovery and Data Mining Cup 1999 (KDD Cup ’99) dataset. …”
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  8. 8
    Medical diagnosis using data mining techniques / Shaiful Nizam Zamri

    Medical diagnosis using data mining techniques / Shaiful Nizam Zamri by Shaiful Nizam , Zamri

    Published 2003
    “…Secondly, this report will review the literature part which started with basic knowledge of data mining and knowing what the basic information about data mining. …”
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    Thesis
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  9. 9
    Towards lowering computational power in IoT systems: Clustering algorithm for high-dimensional data stream using entropy window reduction

    Towards lowering computational power in IoT systems: Clustering algorithm for high-dimensional data stream using entropy window reduction by Alkawsi G., Al-amri R., Baashar Y., Ghorashi S., Alabdulkreem E., Kiong Tiong S.

    Published 2024
    Article
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  10. 10
    Feature selection algorithms for Malaysian dengue outbreak detection model

    Feature selection algorithms for Malaysian dengue outbreak detection model by Husam I.S. Abuhamad, Azuraliza Abu Bakar, Suhaila Zainudin, Mazura Sahani, Zainudin Mohd Ali

    Published 2017
    “…Many studies have been conducted to model and predict dengue outbreak using different data mining techniques. This research aimed to identify the best features that lead to better predictive accuracy of dengue outbreaks using three different feature selection algorithms; particle swarm optimization (PSO), genetic algorithm (GA) and rank search (RS). …”
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  11. 11
    An enhanced classification framework for intrusions detection system using intelligent exoplanet atmospheric retrieval algorithm

    An enhanced classification framework for intrusions detection system using intelligent exoplanet atmospheric retrieval algorithm by Slamet, ., Izzeldin Ibrahim, Mohamed Abdelaziz

    Published 2022
    “…Currently, many companies use data mining for various implementations. One form of implementation is intrusion detection system (IDS). …”
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  12. 12
    Data Classification and Its Application in Credit Card Approval

    Data Classification and Its Application in Credit Card Approval by Thai , VinhTuan

    Published 2004
    “…An analysis on the field of data mining is done to show how data mining, especially data classification, can help in businesses such as targeted marketing, credit card approval, fraud detection, medical diagnosis, and scientific work. …”
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    Final Year Project
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  13. 13
    Improved Malware detection model with Apriori Association rule and particle swarm optimization

    Improved Malware detection model with Apriori Association rule and particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

    Published 2019
    “…In order to improve the detection rate of malicious application on the Android platform, a novel knowledge-based database discovery model that improves apriori association rule mining of a priori algorithm with Particle Swarm Optimization (PSO) is proposed. …”
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  14. 14
    Intrusion detection system for the internet of things based on blockchain and multi-agent systems

    Intrusion detection system for the internet of things based on blockchain and multi-agent systems by Liang, Chao, Shanmugam, Bharanidharan, Azam, Sami, Karim, Asif, Islam, Ashraful, Zamani, Mazdak, Kavianpour, Sanaz, Idris, Norbik Bashah

    Published 2020
    “…The National security lab-knowledge discovery and data mining NSL-KDD dataset is used to test the system. …”
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  15. 15
    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data

    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Ismail, Saidatul Akmar, Mahdin, Hairulnizam

    Published 2023
    “…Overall, most methods have shown an excellent ability to tackle the curse of dimensionality and multivariate features to perform anomaly detection. Moreover, a comparison of each algorithm for anomaly detection is also provided to produce a better algorithm. …”
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  16. 16
    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data

    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Ismail, Saidatul Akmar, Mahdin, Hairulnizam

    “…Overall, most methods have shown an excellent ability to tackle the curse of dimensionality and multivariate features to perform anomaly detection. Moreover, a comparison of each algorithm for anomaly detection is also provided to produce a better algorithm. …”
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  17. 17
    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data

    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Ismail, Saidatul Akmar, Mahdin, Hairulnizam

    Published 2023
    “…Overall, most methods have shown an excellent ability to tackle the curse of dimensionality and multivariate features to perform anomaly detection. Moreover, a comparison of each algorithm for anomaly detection is also provided to produce a better algorithm. …”
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  18. 18
    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data

    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Ismail, Saidatul Akmar, Mahdin, Hairulnizam

    Published 2023
    “…Overall, most methods have shown an excellent ability to tackle the curse of dimensionality and multivariate features to perform anomaly detection. Moreover, a comparison of each algorithm for anomaly detection is also provided to produce a better algorithm. …”
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  19. 19
    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data

    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Ismail, Saidatul Akmar, Mahdin, Hairulnizam

    Published 2023
    “…Overall, most methods have shown an excellent ability to tackle the curse of dimensionality and multivariate features to perform anomaly detection. Moreover, a comparison of each algorithm for anomaly detection is also provided to produce a better algorithm. …”
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  20. 20
    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data

    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Akmar Ismail, Saidatul, Mahdin, Hairulnizam

    Published 2023
    “…Overall, most methods have shown an excellent ability to tackle the curse of dimensionality and multivariate features to perform anomaly detection. Moreover, a comparison of each algorithm for anomaly detection is also provided to produce a better algorithm. …”
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