Abstract
Along with technological developments we observe an increasing amount of stored and processed data. It is not possible to store all incoming data and analyze it on the fly. Therefore many researchers are working on new algorithms for data stream mining. New algorithm should be fast and should use a small amount of memory. We will consider the problem of data stream classification. To increase the accuracy we propose to use an ensemble of classifiers based on a modified FID3 algorithm. The experimental results show that this algorithm is fast and accurate. Therefore it is adequate tool for data stream classification.
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Pietruczuk, L., Duda, P., Jaworski, M. (2012). A New Fuzzy Classifier for Data Streams. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2012. Lecture Notes in Computer Science(), vol 7267. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29347-4_37
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DOI: https://doi.org/10.1007/978-3-642-29347-4_37
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