Detecting outliers in rule-based knowledge bases using Self-Organizing Map and Local Outlier Factor algorithms

Author:

Horyń Czesław,Brzezińska Agnieszka Nowak

Publisher

Elsevier BV

Subject

General Engineering

Reference26 articles.

1. Improving the Efficiency of Genetic-Based Incremental Local Outlier Factor Algorithm for Network Intrusion Detection, part of the Transactions on Computational Science and Computational Intelligence book series (TRACOSCI);Alghushairy,2021

2. A Review of Local Outlier Factor Algorithms for Outlier Detection in Big Data Streams;Alghushairy;Big Data and Cogn. Comput.,2021

3. Bazan J. G., Nguyen H.S., Nguyen S. H., Synak P., Wróblewski J., (2000), Rough set algorithms in classification problem, In: Polkowski L., Tsumoto S., Lin T.Y. (eds.), Rough Set Methods and Applications, Physica-Verlag, Heidelberg, pp. 49–88, https://doi.org/10.1007/ 978-3-7908-1840-6_3

4. RSES and RSESlib - a collection of tools for rough set computations;Bazan,2000

5. LOF: identifying density-based local outliers;Breunig,2000

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