Outlier detection using iterative adaptive mini-minimum spanning tree generation with applications on medical data
Frontiers in Physiology, vol. 14, pp. 1233341
Abstract
As an important technique for data pre-processing, outlier detection plays a crucial role in various real applications and has gained substantial attention, especially in medical fields. Despite the importance of outlier detection, many existing methods are vulnerable to the distribution of outliers and require prior knowledge, such as the outlier proportion. To address this problem to some extent, this article proposes an adaptive mini-minimum spanning tree-based outlier detection (MMOD) method, which utilizes a novel distance measure by scaling the Euclidean distance. For datasets containing different densities and taking on different shapes, our method can identify outliers without prior knowledge of outlier percentages. The results on both real-world medical data corpora and intuitive synthetic datasets demonstrate the effectiveness of the proposed method compared to state-of-the-art methods.
Authors 6
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Leiden University · Second Affiliated Hospital of Xi'an Jiaotong University · Xi'an Jiaotong University
Affiliation as printed
Department of Geriatric Surgery, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
Leiden Institute of Advanced Computer Science, Leiden University, Leiden, Netherlands
School of Software Engineering, Xi'an Jiaotong University, Xi'an, China
School of Software Engineering, Xi’an Jiaotong University, Xi’an, China
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Leiden University · Second Affiliated Hospital of Xi'an Jiaotong University · Xi'an Jiaotong University
Affiliation as printed
Department of Geriatric Surgery, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
Leiden Institute of Advanced Computer Science, Leiden University, Leiden, Netherlands
School of Software Engineering, Xi'an Jiaotong University, Xi'an, China
Department of Geriatric Surgery, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
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Affiliation as printed
MOE Key Lab of Intelligent Network and Network Security, Xi'an Jiaotong University, Xi'an, China
School of Software Engineering, Xi'an Jiaotong University, Xi'an, China
MOE Key Lab of Intelligent Network and Network Security, Xi’an Jiaotong University, Xi’an, China
School of Software Engineering, Xi’an Jiaotong University, Xi’an, China
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Affiliation as printed
Leiden Institute of Advanced Computer Science, Leiden University, Leiden, Netherlands
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Affiliation as printed
Cognitive Systems Lab, University of Bremen, Bremen, Germany
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Hui Liu corresponding
Affiliation as printed
Cognitive Systems Lab, University of Bremen, Bremen, Germany
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