Abstract
Decision tree algorithms such as See5 (or C5) are typically used in data mining for classification and prediction purposes. In this study we propose EXPLORE, a novel decision tree algorithm, which is a modification of See5. The modifications are made to improve the capability of a tree in extracting hidden patterns. Justification of the proposed modifications is also presented. We experimentally compare EXPLORE with some existing algorithms such as See5, REPTree and J48 on several issues including quality of extracted rules/patterns, simplicity, and classification accuracy of the trees. Our initial experimental results indicate advantages of EXPLORE over existing algorithms.
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© 2012 Springer-Verlag Berlin Heidelberg
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Islam, M.Z. (2012). EXPLORE: A Novel Decision Tree Classification Algorithm. In: MacKinnon, L.M. (eds) Data Security and Security Data. BNCOD 2010. Lecture Notes in Computer Science, vol 6121. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25704-9_7
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DOI: https://doi.org/10.1007/978-3-642-25704-9_7
Publisher Name: Springer, Berlin, Heidelberg
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