An improved semisupervised outlier detection algorithm based on adaptive feature weighted clustering

DOI10.1155/2016/6394253zbMath1400.62130OpenAlexW2567596697WikidataQ59140879 ScholiaQ59140879MaRDI QIDQ1793446

Jinhong Yang, Ting-Quan Deng

Publication date: 12 October 2018

Published in: Mathematical Problems in Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2016/6394253

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Robustness and adaptive procedures (parametric inference) (62F35)

Uses Software

• UCI-ml
• LOF

Cites Work

• Inter-image outliers and their application to image classification
• Support vector data description
• A boundary method for outlier detection based on support vector domain description
• Semi-supervised outlier detection based on fuzzy rough \(c\)-means clustering
• A precise ranking method for outlier detection
• A survey of outlier detection methodologies
• Estimating the Support of a High-Dimensional Distribution
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