In this paper, a weighted subspace anomaly detection (WSAD) method is proposed. The proposed WSAD method can find the underlying subspaces for the normal data ...
Weighted subspace anomaly detection in high-dimensional space
dl.acm.org › doi › j.patcog.2023.110056
Feb 1, 2024 · Anomaly detection aims at finding anomalies deviating from the normal data patterns. Virtually all anomaly detection methods create a model ...
Oct 22, 2024 · In this paper, a new method for anomaly detection based on weighted clustering is proposed. The weights that were obtained by summing the ...
Dec 16, 2024 · Weighted subspace anomaly detection in high-dimensional space ,Science hub Mutual Aid community.
Aug 9, 2023 · This method generates weighted subspaces and dimensions for data objects, reducing the impact of noise created by high-dimensional data and ...
In high-dimensional space, the data becomes sparse, and the true outliers become masked by the noise effects of multiple irrelevant dimensions, when analyzed in ...
Mar 24, 2022 · High-dimensional space may exist many subspaces, and anomalies may exist any subspaces. A brute-force method is computationally prohibitive ...
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The random subspace method generates multiple individual classifiers by projecting the original feature space into different subspaces. The projection from the ...
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In this paper, we propose a method with twice dimension-projections, which integrates primary subspace outlier detection and secondary point-projection between ...
A new outlier detection algorithm called EOEH (Ensemble Outlier Detection Method Based on Information Entropy-Weighted Subspaces for High-Dimensional Data)