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Contrast Data Mining: Concepts, Algorithms, and Applications (Chapman & Hall/CRC Data Mining and Knowledge Discovery)
Computers & Internet

Contrast Data Mining: Concepts, Algorithms, and Applications (Chapman & Hall/CRC Data Mining and Knowledge Discovery)

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"Contrast data mining : concepts, algorithms, and applications" by Guozhu Dong; James Bailey, published by CRC Press Taylor & Francis Group. ''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''-- Read more... Book details: xxiv, 410 pagesustrations ; 25 cm pages. Order now on BookShops.in with fast, reliable delivery across India.

Book Specifications

ISBN-139781439854327
ISBN-101439854327
PublisherChapman & Hall
Languageenglish
Print Length434 pages
CategoryComputers & Internet

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