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Titlebook: Statistical Implicative Analysis; Theory and Applicati Régis Gras,Einoshin Suzuki,Filippo Spagnolo Book 2008 Springer-Verlag Berlin Heidelb

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Fictitious Pupils and Implicative Analysis: a Case Studylicative Analysis. On the one hand, unlike supplementary variables, the fact of adding fictitious data to the sample does modify analyses results, so caution is needed. On the other hand, . are a tool for better understanding the data structure resulting from the analyses.
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Book 2008of 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 artific
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1860-949X lysis 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 implicatio
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Inducing and Evaluating Classification Trees with Statistical Implicative Criteriahe second usage relies upon the strength of implication for assigning the most appropriate conclusion to each leaf of the induced tree. We demonstrate the practical usefulness of this statistical implicative view on decision trees through a full scale real world application.
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Statistical Implicative Analysis of DNA microarraysod is applied to the most challenging problems encountered in gene expression analysis, namely the discovery of gene coregulation, gene selection and tumour classification. We compare our method with performing algorithms that are dedicated to gene expression data or that are well-suited to high-dimensional variable space.
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