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  2. Support vector machine - Wikipedia

    en.wikipedia.org/wiki/Support_vector_machine

    The soft-margin support vector machine described above is an example of an empirical risk minimization (ERM) algorithm for the hinge loss. Seen this way, support vector machines belong to a natural class of algorithms for statistical inference, and many of its unique features are due to the behavior of the hinge loss.

  3. Structured support vector machine - Wikipedia

    en.wikipedia.org/wiki/Structured_support_vector...

    The structured support-vector machine is a machine learning algorithm that generalizes the Support-Vector Machine (SVM) classifier. Whereas the SVM classifier supports binary classification , multiclass classification and regression , the structured SVM allows training of a classifier for general structured output labels .

  4. Kernel method - Wikipedia

    en.wikipedia.org/wiki/Kernel_method

    In machine learning, kernel machines are a class of algorithms for pattern analysis, whose best known member is the support-vector machine (SVM). These methods involve using linear classifiers to solve nonlinear problems. [ 1 ]

  5. Vladimir Vapnik - Wikipedia

    en.wikipedia.org/wiki/Vladimir_Vapnik

    Vladimir Naumovich Vapnik (Russian: Владимир Наумович Вапник; born 6 December 1936) is a computer scientist, researcher, and academic.He is one of the main developers of the Vapnik–Chervonenkis theory of statistical learning [1] and the co-inventor of the support-vector machine method and support-vector clustering algorithms.

  6. Category:Support vector machines - Wikipedia

    en.wikipedia.org/wiki/Category:Support_vector...

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  7. Radial basis function kernel - Wikipedia

    en.wikipedia.org/wiki/Radial_basis_function_kernel

    Because support vector machines and other models employing the kernel trick do not scale well to large numbers of training samples or large numbers of features in the input space, several approximations to the RBF kernel (and similar kernels) have been introduced. [4]

  8. List of algorithms - Wikipedia

    en.wikipedia.org/wiki/List_of_algorithms

    Relevance-Vector Machine (RVM): similar to SVM, but provides probabilistic classification; Supervised learning: Learning by examples (labelled data-set split into training-set and test-set) Support Vector Machine (SVM): a set of methods which divide multidimensional data by finding a dividing hyperplane with the maximum margin between the two sets

  9. Least-squares support vector machine - Wikipedia

    en.wikipedia.org/wiki/Least-squares_support...

    Least-squares support-vector machines (LS-SVM) for statistics and in statistical modeling, are least-squares versions of support-vector machines (SVM), which are a set of related supervised learning methods that analyze data and recognize patterns, and which are used for classification and regression analysis.