Abstract
In this work we show the research track and the current results about the application of structured parallel programming tools to dev elop scalable data-mining applications. We discuss the exploitation of the divide and conquer nature of the well kno wn C4.5 classification algorithm in spite of its in-core memory requirements. The opportunity of applying external memory techniques to manage the data is advocated. Current results of the experiments are reported ?© 2000 Springer-Verlag Berlin Heidelberg.
Cite
CITATION STYLE
Becuzzi, P., Coppola, M., Ruggieri, S., & Vanneschi, M. (2000). Parallelisation of C4.5 as a particular divide and conquer computation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1800 LNCS, pp. 382–389). Springer Verlag. https://doi.org/10.1007/3-540-45591-4_50
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