Quality measures in data mining
著者
書誌事項
Quality measures in data mining
(Studies in computational intelligence, v. 43)
Springer, c2007
大学図書館所蔵 件 / 全4件
-
該当する所蔵館はありません
- すべての絞り込み条件を解除する
内容説明・目次
内容説明
This book presents recent advances in quality measures in data mining.
目次
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.
「Nielsen BookData」 より