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  1. 1
    The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model

    The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model by Nur Faraidah, Muhammad Di, Siti Zanariah, Satari

    Published 2017
    “…In this study, we proposed multiple outliers detection in circular regression models based on the clustering algorithm. …”
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  2. 2
    Comparative study of clustering-based outliers detection methods in circular-circular regression model

    Comparative study of clustering-based outliers detection methods in circular-circular regression model by Siti Zanariah, Satari, Nur Faraidah, Muhammad Di, Yong Zulina, Zubairi, Abdul Ghapor, Hussin

    Published 2021
    “…This paper is a comparative study of several algorithms for detecting multiple outliers in circular-circular regression model based on the clustering algorithms. …”
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  3. 3
    Comparative study of clustering-based outliers detection methods in circular-circular regression model

    Comparative study of clustering-based outliers detection methods in circular-circular regression model by Siti Zanariah Satari, Nur Faraidah Muhammad Di, Yong Zulina Zubairi, Abdul Ghapor Hussin

    Published 2021
    “…This paper is a comparative study of several algorithms for detecting multiple outliers in circular-circular regression model based on the clustering algorithms. …”
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  4. 4
    Comparative study of clustering-based outliers detection methods in circularcircular regression model

    Comparative study of clustering-based outliers detection methods in circularcircular regression model by Siti Zanariah, Satari, Nur Faraidah, Muhammad Di, Yong Zulina, Zubairi, Abdul Ghapor, Hussin

    Published 2021
    “…This paper is a comparative study of several algorithms for detecting multiple outliers in circular-circular regression model based on the clustering algorithms. …”
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  5. 5
    The multiple outliers detection for circular univariate data using different agglomerative clustering algorithms

    The multiple outliers detection for circular univariate data using different agglomerative clustering algorithms by Nur Syahirah, Zulkipli, Siti Zanariah, Satari, Wan Nur Syahidah, Wan Yusoff

    Published 2024
    “…This study proposes the procedure of detecting multiple outliers, particularly for univariate circular data based on agglomerative clustering algorithms. …”
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  6. 6
    Adaptive grid-meshed-buffer clustering algorithm for outlier detection in evolving data stream

    Adaptive grid-meshed-buffer clustering algorithm for outlier detection in evolving data stream by Abdulateef, Alaa Fareed

    Published 2023
    “…This research introduces Adaptive Grid-Meshed-Buffer Stream Clustering Algorithm (AGMB), that addresses these weaknesses and improves outlier detection. …”
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  7. 7
    The effect of different similarity distance measures in detecting outliers using single-linkage clustering algorithm for univariate circular biological data

    The effect of different similarity distance measures in detecting outliers using single-linkage clustering algorithm for univariate circular biological data by Nur Syahirah, Zulkipli, Siti Zanariah, Satari, Wan Nur Syahidah, Wan Yusoff

    “…Clustering algorithms can be used to create an outlier detection procedure in univariate circular data. …”
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  8. 8
    Single-linkage method to detect multiple outliers with different outlier scenarios in circular regression model

    Single-linkage method to detect multiple outliers with different outlier scenarios in circular regression model by Siti Zanariah, Satari, Nur Faraidah, Muhammad Di, Roslinazairimah, Zakaria

    Published 2018
    “…Single-linkage is one of the algorithms in agglomerative clustering technique that can be used to detect outliers. …”
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  9. 9
    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
    “…In this paper we will explain the first part of our research, which is focused on outlier identification and provide a description of why an identified outlier exceptional, based on Distance-Based outlier detection and Density-Based outlier detection.…”
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  10. 10
    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
    “…The simulation results indicate that the proposed method is suitable to detect a single outlier. As for the multiple outliers, a clustering algorithm is considered and a dendogram to visualise the clustering algorithm is used. …”
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  11. 11
    Machine Learning Approaches to Advanced Outlier Detection in Psychological Datasets

    Machine Learning Approaches to Advanced Outlier Detection in Psychological Datasets by Abri K.Al., Sidhu M.S.

    Published 2025
    “…Our initial findings showed 155 outliers by both LOF and IF and 147 by OCSVM. A deeper analysis revealed that LOF detected 55 unique outliers based on differences in local density, OCSVM isolated 44 unique outliers utilizing its transformed feature space, and IF identified 76 unique outliers leveraging its tree-based mechanics. …”
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  12. 12
    Automatic filtering of far outliers in multibeam echo sounding dataset using robust detection algorithms

    Automatic filtering of far outliers in multibeam echo sounding dataset using robust detection algorithms by Mahmud, Mohd. Razali, Mohd. Yusof, Othman

    Published 2005
    “…This paper elaborates the techniques used for the detection and elimination of the far outliers in the MBES dataset, known as robust detection algorithms. …”
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  13. 13
    Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares

    Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares by Uraibi, Hassan Sami

    Published 2009
    “…To rectify this problem, we propose a Dynamic Robust Bootstrap-LTS based (DRBLTS) algorithm where the percentage of outliers in each bootstrap sample is detected. …”
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  14. 14
    An Evolutionary Stream Clustering Technique for Outlier Detection

    An Evolutionary Stream Clustering Technique for Outlier Detection by Supardi, N.A., Abdulkadir, S.J., Aziz, N.

    Published 2020
    “…Later, this algorithm will be extended to optimize the model in detecting outlier on data streams. …”
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  15. 15
    Detection of multiple outliners in linear regression using nonparametric methods

    Detection of multiple outliners in linear regression using nonparametric methods by Adnan, Robiah

    Published 2004
    “…There have been considerable interest in recent years in the detection and accommodation of multiple outliers in linear regression. …”
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  16. 16
    Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data

    Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data by Baba, Ishaq Abdullahi

    Published 2022
    “…The proposed algorithm has been applied to detect outliers in the high dimensional data. …”
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  17. 17
    Improved robust estimator and clustering procedures for multivariate outliers detection

    Improved robust estimator and clustering procedures for multivariate outliers detection by Sharifah Sakinah, Syed Abd Mutalib

    Published 2023
    “…One of the methods to detect outliers in multivariate data is by using distance-based methods, which is Mahalanobis distance (MD). …”
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  18. 18
    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
    “…Some researchers opt to perform pre-pruning or post-pruning of the CART in handling the outliers. This study proposes a modified classification tree algorithm called Winsorize tree based on the distribution of classes in the training dataset. …”
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  19. 19
    Modified sequential fences for identifying univariate outliers

    Modified sequential fences for identifying univariate outliers by Wong, Hui Shein

    Published 2016
    “…The modified sequential fences method is found can accurately detect the outliers in positively skewed distribution. …”
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  20. 20
    A clustering-based method for outlier detection under concept drift

    A clustering-based method for outlier detection under concept drift by Tahir, Mahjabeen, Abdullah, Azizol, Udzir, Nur Izura, Kasmiran, Khairul Azhar

    Published 2024
    “…The proposed approach CADSD (Cluster-based Anomaly Detection with Streaming Data), operates in real-time without pre-training. …”
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