03197cam a2200373 i 4500 10112819 OSt 20150408114135.0 m d cr n 130803s2013 flua | b 001 0 eng d 9781439854327 (hardback : acidfree paper) (WaSeSS)ssj0000755359 Ma-Un eng 006.312 23 COD Contrast data mining Contrast data mining concepts, algorithms, and applications / edited by Guozhu Dong and James Bailey. Boca Raton : CRC Press, Taylor & Francis Group 2013. xxiv, 410 p. : ill ; 25 cm. Chapman & Hall/CRC data mining and knowledge discovery series Includes bibliographical references (pages 363-402) and index. License restrictions may limit access. "Preface Contrasting is one of the most basic types of analysis. Contrasting based analysis is routinely employed, often subconsciously, by all types of people. People use contrasting to better understand the world around them and the challenging problems they want to solve. People use contrasting to accurately assess the desirability of important situations, and to help them better avoid potentially harmful situations and embrace potentially beneficial ones. Contrasting involves the comparison of one dataset against another. The datasets may represent data of different time periods, spatial locations, or classes, or they may represent data satisfying different conditions. Contrasting is often employed to compare cases with a desirable outcome against cases with an undesirable one, for example comparing the benign and diseased tissue classes of a cancer, or comparing students who graduate with university degrees against those who do not. Contrasting can identify patterns that capture changes and trends over time or space, or identify discriminative patterns that capture differences among contrasting classes or conditions. Traditional methods for contrasting multiple datasets were often very simple so that they could be performed by hand. For example, one could compare the respective feature means, compare the respective attribute-value distributions, or compare the respective probabilities of simple patterns, in the datasets being contrasted. However, the simplicity of such approaches has limitations, as it is difficult to use them to identify specific patterns that offer novel and actionable insights, and identify desirable sets of discriminative patterns for building accurate and explainable classifiers"-- Contrast data mining. 36346 BUSINESS & ECONOMICS / Statistics. bisacsh 36347 COMPUTERS / Database Management / Data Mining. bisacsh 36348 COMPUTERS / Programming / Algorithms. bisacsh 36349 Dong, Guozhu, 1957- 36350 Bailey, James, 1971 June 30- 36351 STATSnetBASE http://www.columbia.edu/cgi-bin/cul/resolve?clio10112819 Full text available from STATSnetBASE Library of Congress record ddc BOOK 30257 264757 0 2013-08-03 0 1 006.312 COD 1 2013-08-03 CL 00206020 CL 2013-08-03 00:00:00 BOOK ddc 0 0 2013-08-03 0 0 006.312 COD 2 2013-08-03 CL 00206019 CL 2013-08-03 00:00:00 BOOK ddc 0 0 2013-08-03 0 0 006.312 COD 3 2013-08-03 CL 00206018 CL 2013-08-03 00:00:00 BOOK ddc 0