Statistical data mining and knowledge discovery

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statistical data mining and knowledge discovery

Statistical Data Analytics: Foundations for Data Mining, Informatics, and Knowledge Discovery by Walter W. Piegorsch

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Data mining and knowledge discovery, and how to discover patterns and relationships

Statistical Data Mining and Knowledge Discovery

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Skip to Main Content. A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity. Use of this web site signifies your agreement to the terms and conditions. Personal Sign In. For IEEE to continue sending you helpful information on our products and services, please consent to our updated Privacy Policy. Email Address. Sign In.

Data mining is the process of discovering patterns in large data sets involving methods at the intersection of machine learning , statistics , and database systems. The term "data mining" is a misnomer , because the goal is the extraction of patterns and knowledge from large amounts of data, not the extraction mining of data itself.
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Lecture - 35 Data Mining and Knowledge Discovery Part II

Data mining and knowledge discovery is the principle of analyzing large amounts of data and picking out relevantinformation leading to the knowledge discovery process for extracting meaningful patterns, rules and models from raw data making discovered patternsunderstandable. Applications include medicine, politics, games, business, marketing, bioinformatics and many other areas of science and engineering. It isan area of research activity that stands at the intellectual intersection of statistics, computer science, machine learning and database management. Itdeals with very large datasets, tries to make fewer theoretical assumptions than has traditionally been done in statistics, and typically focuses onproblems of classification, prediction, description and profiling, clustering, and regression. Skip to main content Skip to table of contents. Encyclopedia of Complexity and Systems Science Edition. Editors: Robert A.

Use the link below to share a full-text version of this article with your friends and colleagues. Learn more. Knowledge discovery and data mining are the landmarks of the information age. Acquiring, storing, and understanding data have posed great challenges and brought a lot of promises. Knowledge discovery in databases KDD and data mining DM have emerged as high profile, rapidly evolving, badly needed, conceptually advanced, and practically important areas. In a nutshell, KDD and DM have to deal with a truly remarkable diversity of data and a panoply of applications.

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  1. Statistical Data Mining and Knowledge Discovery brings together a stellar panel of experts to discuss and disseminate recent developments in.

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