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This book presents recent advances in quality measures in data mining.

This book presents recent advances in quality measures in data mining.
  • Produktdetails
  • Studies in Computational Intelligence 43
  • Verlag: Springer / Springer Berlin Heidelberg / Springer, Berlin
  • Artikelnr. des Verlages: 11588535
  • Erscheinungstermin: 8. Januar 2007
  • Englisch
  • Abmessung: 244mm x 161mm x 25mm
  • Gewicht: 640g
  • ISBN-13: 9783540449119
  • ISBN-10: 3540449116
  • Artikelnr.: 20946622
Overviews on rule quality.- Choosing the Right Lens: Finding What is Interesting in Data Mining.- A Graph-based Clustering Approach to Evaluate Interestingness Measures: A Tool and a Comparative Study.- Association Rule Interestingness Measures: Experimental and Theoretical Studies.- On the Discovery of Exception Rules: A Survey.- From data to rule quality.- Measuring and Modelling Data Quality for Quality-Awareness in Data Mining.- Quality and Complexity Measures for Data Linkage and Deduplication.- Statistical Methodologies for Mining Potentially Interesting Contrast Sets.- Understandability of Association Rules: A Heuristic Measure to Enhance Rule Quality.- Rule quality and validation.- A New Probabilistic Measure of Interestingness for Association Rules, Based on the Likelihood of the Link.- Towards a Unifying Probabilistic Implicative Normalized Quality Measure for Association Rules.- Association Rule Interestingness: Measure and Statistical Validation.- Comparing Classification Results between N-ary and Binary Problems.