Statistical implicative analysis: theory and applications/ edited by Regis Gras, Einoshin Suzuki, Fabric Guillet and Filippo Spagnolo
Material type: TextSeries: Studies in Computational Intelligence, 127Publication details: London: Springer, 2008Description: xv, 513 p. : ill. ; 25 cmISBN: 9783540789826Subject(s): Mathematical analysis | Statistics | Data mining | Mathematics | Artificial intelligence | Engineering | Engineering mathematicsDDC classification: 519.5Item type | Current library | Call number | Status | Date due | Barcode | Item holds |
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General Books | Central Library, Sikkim University General Book Section | 519.5 GRA/S (Browse shelf(Opens below)) | Available | P40965 |
Methodology and concepts for SIA --
An overview of the Statistical Implicative Analysis (SIA) development --
CHIC: Cohesive Hierarchical Implicative Classification --
Assessing the interestingness of temporal rules with Sequential Implication Intensity --
Application to concept learning in education, teaching, and didactics --
Student's Algebraic Knowledge Modelling: Algebraic Context as Cause of Student's Actions --
The graphic illusion of high school students --
Implicative networks of student's representations of Physical Activities --
A comparison between the hierarchical clustering of variables, implicative statistical analysis and confirmatory factor analysis --
Implications between learning outcomes in elementary bayesian inference --
Personal Geometrical Working Space: a Didactic and Statistical Approach --
A methodological answer in various application frameworks --
Statistical Implicative Analysis of DNA microarrays --
On the use of Implication Intensity for matching ontologies and textual taxonomies --
Modelling by Statistic in Research of Mathematics Education --
Didactics of Mathematics and Implicative Statistical Analysis --
Using the Statistical Implicative Analysis for Elaborating Behavioral Referentials --
Fictitious Pupils and Implicative Analysis: a Case Study --
Identifying didactic and sociocultural obstacles to conceptualization through Statistical Implicative Analysis --
Extensions to rule interestingness in data mining --
Pitfalls for Categorizations of Objective Interestingness Measures for Rule Discovery --
Inducing and Evaluating Classification Trees with Statistical Implicative Criteria --
On the behavior of the generalizations of the intensity of implication: A data-driven comparative study --
The TVpercent principle for the counterexamples statistic --
User-System Interaction for Redundancy-Free Knowledge Discovery in Data --
Fuzzy Knowledge Discovery Based on Statistical Implication Indexes.
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