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By Antoine Cornuejols, Laurent Miclet, Yves Kodratoff, Tom Mitchell

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Extra info for Apprentissage artificiel : Concepts et algorithmes

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2 Une methode iterative : l'algorithme de Ho et Kashyap. . . . . . 3 Un autre calcul : l'algorithme du perceptron . . . . 4 L'hyperplan discriminant de Fisher . . . . . . 5 Surfaces separatrices non lineaires . . . . . . 6 Et pour plus de deux classes? . . . . . . . 3 Les separateurs a vastes marges (SVM) . . . . . . . 1 La recherche des separateurs lineaires a vastes marges . 2 Quelle justi cation pour les SVM? . . . . . . 4 Conclusions sur les SVM .

5 Analyse : compression et pouvoir inductif . . . . . . . . 4 L'induction en debat . . . . . . . . . . . . . . . . 1 Le no-free-lunch theorem : toutes les methodes se valent !? . . . 2 Le no-free-lunch theorem et l'analyse de Vapnik : une contradiction? 5 Discussion sur l'analyse classique. Variantes et perspectives . . . . . 1 D'autres modeles d'apprentissage . . . . . . . . . . . 2 D'autres types d'analyses . . . . . . . . . . . . . com) - 27 Octobre 2009 à 09:30 18 Annexes techniques .

7 Les reseaux bayesiens et les modeles graphiques . . . . 8 Les cha^nes de Markov et les modeles de Markov caches . 9 Les grammaires . . . . . . . . . . . . . 10 Les formalismes logiques . . . . . . . . . . 3 La recherche dans l'espace des hypotheses . . . . . . . 1 Caracterisation de l'espace de recherche . . . . . . 2 Caracterisation des fonctions de co^ut . . . . . . . 3 Les methodes d'optimisation . . . . . . . . . 4 L'evaluation de l'apprentissage .

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