Results 11 to 20 of about 84,843 (251)
, 2020 In Proceedings of The 21th International Conference on Web Information Systems Engineering (WISE 2020), Amsterdam and Leiden, The ...
Deepak P 0001, Savitha Sam Abraham
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A Review of Local Outlier Factor Algorithms for Outlier Detection in Big Data Streams
Big Data and Cognitive Computing, 2020 Outlier detection is a statistical procedure that aims to find suspicious events or items that are different from the normal form of a dataset. It has drawn considerable interest in the field of data mining and machine learning.
Omar Alghushairy +3 more
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Outlier detection in BLAST hits [PDF]
Algorithms for Molecular Biology, 2018 An important task in a metagenomic analysis is the assignment of taxonomic labels to sequences in a sample. Most widely used methods for taxonomy assignment compare a sequence in the sample to a database of known sequences. Many approaches use the best BLAST hit(s) to assign the taxonomic label.
Nidhi Shah +2 more
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Attribute Grouping-based Categorical Outlier Detection Using Isolation Forest Ensemble Strategy [PDF]
Jisuanji kexueAttribute grouping is one of the effective steps in high-dimensional outlier detection,but the current ensemble strategies in attribute grouping-based outlier detection only take into account the local outlier information within each attribute group,and ...
SONG Yijing, ZHANG Jifu
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Investigation of outlier detection algorithm
Lietuvos Matematikos Rinkinys, 2005 The proposed outlier factor was used to analyze the multidimensional data sets regarding outlier detection. The paper describes two kinds of investigation: the influence of omitting some part of distances between data points, and the influence of ...
Vydūnas Šaltenis
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Detecting Outliers in Non-IID Data: A Systematic Literature Review
IEEE Access, 2023 Outlier detection (outlier and anomaly are used interchangeably in this review) in non-independent and identically distributed (non-IID) data refers to identifying unusual or unexpected observations in datasets that do not follow an independent and ...
Shafaq Siddiqi +3 more
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Review of Outlier Detection Algorithms [PDF]
Jisuanji kexueOutlier detection,as an important research direction in the field of data mining,aims to discover data points in a dataset that are different from the majority and have potential analytical value,assistresearchers in identifying potential issues in the ...
KONG Lingchao, LIU Guozhu
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A Comparison of Outlier Detection Techniques for High-Dimensional Data
International Journal of Computational Intelligence Systems, 2018 Outlier detection is a hot topic in machine learning. With the newly emerging technologies and diverse applications, the interest of outlier detection is increasing greatly.
Xiaodan Xu +3 more
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A Novel Outlier Detection Model for Vibration Signals Using Transformer Networks
IEEE Access, 2022 Outlier detection in vibration signals can play an important role in addressing the issue of structural or environmental changes during vibration testing. In this study, a transformer-based model for outlier detection is proposed.
Ruiheng Zhang +4 more
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An Incremental Local Outlier Detection Method in the Data Stream
Applied Sciences, 2018 Outlier detection has attracted a wide range of attention for its broad applications, such as fault diagnosis and intrusion detection, among which the outlier analysis in data streams with high uncertainty and infinity is more challenging.
Haiqing Yao +3 more
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