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Boosting of Association Rules for Robust Emergency Detection

Contributo in Atti di convegno
Data di Pubblicazione:
2015
Abstract:
The use of association rules extracted from daily geophysical measures allows for the detection of previously unknown connections between events, including emergency con- ditions. While these rules imply that the presence of a given symbol occurs while a second one is present, their classification performance may vary with respect to test data. We propose to build strong classifiers out of simpler association rules: their use shows promising results with respect to their accuracy.
Tipologia CRIS:
04.01 Contributo in Atti di convegno
Keywords:
Big Data; KDD; Disaster pre
Elenco autori:
Cipolla, Emanuele; Vella, Filippo
Autori di Ateneo:
VELLA FILIPPO
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/306563
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