Abstract
This paper develops an iterative sample based Improved Quick Reduct algorithm with Information Gain heuristic approach for recommending a quality reduct for large decision tables. The Methodology and its performance have been demonstrated by considering large datasets. It is recommended to use roughly 5 to 10% data size for obtaining an apt reduct.
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Sai Prasad, P.S.V.S., Raghavendra Rao, C. (2012). Scalable Improved Quick Reduct: Sample Based. In: Li, T., et al. Rough Sets and Knowledge Technology. RSKT 2012. Lecture Notes in Computer Science(), vol 7414. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31900-6_5
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DOI: https://doi.org/10.1007/978-3-642-31900-6_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31899-3
Online ISBN: 978-3-642-31900-6
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