- Tytuł:
- Negative feature selection algorithm for anomaly detection in real time
- Autorzy:
-
Hryniów, K.
Dzieliński, A. - Powiązania:
- https://bibliotekanauki.pl/articles/92969.pdf
- Data publikacji:
- 2011
- Wydawca:
- Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach
- Tematy:
-
anomaly detection
feature selection
frequent pattern mining
neural networks
rule-based systems - Opis:
- 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.
- Źródło:
-
Studia Informatica : systems and information technology; 2011, 1-2(15); 15-23
1731-2264 - Pojawia się w:
- Studia Informatica : systems and information technology
- Dostawca treści:
- Biblioteka Nauki
Artykuł