The properties of nonuniformity analysis of high dimensional data
A novel approach to outlier detection and clustering on the ground of the distribution of distances between multidimensional points is presented. The basic idea is to eval uate the outlier factor for each data point. A comparison with some popular outlier detection and clustering methods shows the...
Main Author: | Vydūnas Šaltenis |
---|---|
Format: | Article |
Language: | English |
Published: |
Vilnius University Press
2004-12-01
|
Series: | Lietuvos Matematikos Rinkinys |
Subjects: | |
Online Access: | https://www.journals.vu.lt/LMR/article/view/32223 |
Similar Items
-
Investigation of outlier detection algorithm
by: Vydūnas Šaltenis
Published: (2005-12-01) -
Robust subspace methods for outlier detection in genomic data circumvents the curse of dimensionality
by: Omar Shetta, et al.
Published: (2020-02-01) -
A Comparison of Outlier Detection Techniques for High-Dimensional Data
by: Xiaodan Xu, et al.
Published: (2018-01-01) -
An Ensemble Outlier Detection Method Based on Information Entropy-Weighted Subspaces for High-Dimensional Data
by: Zihao Li, et al.
Published: (2023-08-01) -
Advancements of Outlier Detection: A Survey
by: Ji Zhang
Published: (2013-02-01)