Online learning strategies for classification of static data streams

Authors:
M. Millán-Giraldo;J. S. Sánchez
Affiliations:
Universitat Jaume I, Dept. Llenguatges i Sistemes Informátics, Castelló de la Plana, Spain;Universitat Jaume I, Dept. Llenguatges i Sistemes Informátics, Castelló de la Plana, Spain
Venue:
DIWEB'08 Proceedings of the 8th WSEAS international conference on Distance learning and web engineering
Year:
2008

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Abstract

This paper addresses the problem of online learning for static streaming data. The ultimate objective is to compare a number of very simple learning methods, mainly taken from the literature. We include a straightforward time-weighted strategy for forgetting obsolete objects from the reference set. Experiments are conducted on ten real data sets and using five different classifiers in order to identify which online learning model is the most suitable in terms of classifier performance.