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Springer Statistical Implicative Analysis: Theory and Applications: 127 (Studies in Computational Intelligence, 127)

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Description

Statistical implicative analysis is a data analysis method with a significant impact on a variety of areas ranging from pedagogical research to data mining. This volume collects significant research contributions from disciplines that benefit from SIA. From the Back Cover Statistical implicative analysis is a data analysis method created by Régis Gras almost thirty years ago which has a significant impact on a variety of areas ranging from pedagogical and psychological research to data mining. Statistical implicative analysis (SIA) provides a framework for evaluating the strength of implications; such implications are formed through common knowledge acquisition techniques in any learning process, human or artificial. This new concept has developed into a unifying methodology, and has generated a powerful convergence of thought between mathematicians, statisticians, psychologists, specialists in pedagogy and last, but not least, computer scientists specialized in data mining. This volume collects significant research contributions of several rather distinct disciplines that benefit from SIA. Contributions range from psychological and pedagogical research, bioinformatics, knowledge management, and data mining.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
25 November 2010
Listed Since
20 September 2010

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