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Extra resources for Artificial Neural Networks - A Tutorial

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Application In this section CCEC, RL, DT and DA are used to generate the domain decision model for P4. The interpretation provided by the experts in [8] was supported by the concepts induced by CCEC[7], which identifies variables that distinguish every cluster. 1. Logistic Regression (LR) SPSS is used to apply a LR to the data and the following equations were obtained for each cluster. On the right, between brackets, the level of correctness1. From these equations, variable relationships determining P(C=1) for each cluster can be identified : first equation shows that high values of SS-E and DBO-E increase P (C383 = 1) as low value of DBO-S also does.

9, pp. 12–12, 10 2003. [8] N. Oza and S. Russell, “Online bagging and boosting,” in Artificial Intelligence and Statistics 2001. Morgan Kaufmann, 2001, pp. 105–112. Artificial Intelligence Research and Development M. Polit et al. ) IOS Press, 2006 © 2006 The authors and IOS Press. 19 Support Vector Machines for color adjustment in automotive basecoat Francisco RUIZ*, Cecilio ANGULO** and Núria AGELL* *Fundació ESADE, Avda. Pedralbes, 60-62, Barcelona, Spain **Universitat Politecnica de Catalunya, Avda.

Decision Support Systems (DSS) based on artificial intelligence techniques have in recent years demonstrated their efficiency in situations in which there is no 20 F. Ruiz et al. / Support Vector Machines for Color Adjustment in Automotive Basecoat exhaustive information on the process [2]. Such systems start off from an empirical and partial knowledge of this process, and allow the extraction of regularities and predictions in unknown situations. In color matching, commercial soft-computing DSS tools have been developed to help in the task of color formulation.

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Artificial Neural Networks - A Tutorial by Jain

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