Road map linear discrimination: the separable case



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tarix29.10.2017
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Support Vector Machines S.V.M. Special session


radial SVM



Road map

  • linear discrimination: the separable case

  • linear discrimination: the NON separable case

  • quadratic discrimination

  • radial SVM

    • principle
    • 3 regularization hyperparametres
    • some benchmark results (glass data)
  • SMV for regression



What ’s new with SVM



Space functional



Minimization with constraints



Minimization with constraints dual formulation



Linear discrimination the separable case



Linear discrimination the separable case



Linear discrimination the separable case



Linear discrimination the separable case



Linear discrimination the separable case



Linear classification- the separable case



Equality constraint integration



Inequality constraint integration



Linear classification : the non separable case



quadratic SVM



polynomial classification



Gaussian Kernel based S.V.M.



1 d example



3 regularization parameters

  • C : the superior bound

  •  : the kernel bandwidth: K(x,y)

  • the linear system regularization

    • H=b => (H+I)=b


Small bandwidth and large C



Large bandwidth and large C



Large bandwidth and small C



SVM for regression



Example...



 small and  also



Geostatistics



An other way to see things (Girosi, 97)



SVM history and trends



Optimization issues QP with constraints



Optimization issues



Some benchmark considerations (Platt 98)



open issues



Books in Support Vector Research



Events in Support Vector Research



Conclusion



Kataloq: ~scanu
~scanu -> Dea perception et Traitement de l’Information Reconnaissance des formes
~scanu -> Réseaux de neurones artificiels «programmation par l’exemple» S. Canu, laboratoire psi, insa de Rouen
~scanu -> S. Canu, Ph. Leray, A. Rakotomamonjy laboratoire psi
~scanu -> Intelligent sensor and learning challenges for context aware appliances >> Stéphane Canu
~scanu -> Algorithmes d’apprentissage rapide pour les réseaux neuronaux multi-couches
~scanu -> Réseaux de neurones artificiels «le neurone formel» S. Canu, laboratoire psi, insa de Rouen
~scanu -> Outils d’analyse statistiques «programmation par l’exemple» S. Canu, laboratoire psi, insa de Rouen
~scanu -> Réseaux de neurones artificiels «la rétropropagation du gradient» S. Canu, laboratoire psi, insa de Rouen
~scanu -> Dea perception et Traitement de l’Information Reconnaissance des formes
~scanu -> Khoufi Héla,Poinsignon Jean-Marc dea icsv tp1: étude bibliographique

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