Negative feature selection algorithm for anomaly detection in real time

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Title Negative feature selection algorithm for anomaly detection in real time
Autor: Hryniów, Krzysztof; Dzieliński, Andrzej
URI: http://hdl.handle.net/11331/3404
Date: 2011
Źródło: Studia Informatica : systemy i technologie informacyjne. Nr 15 (2011), s. 15-23
Abstract: Anomaly detection methods are of common use in many fields, including databases and large computer systems. This article presents new algorithm based on negative feature selection, which can be used to find anomalies in real time. Proposed algorithm, called Negative Feature Selection algorithm (NegFS) can be also used as first step for preprocessing data analyzed by neural networks, rule-based systems or other anomaly detection tools, to speed up the process for large and very large datasets of different types.

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Uznanie autorstwa-Na tych samych warunkach 3.0 Polska Except where otherwise noted, this item's license is described as Uznanie autorstwa-Na tych samych warunkach 3.0 Polska

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