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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. Ranking SVM - Wikipedia

    en.wikipedia.org/wiki/Ranking_SVM

    The ranking SVM algorithm is a learning retrieval function that employs pairwise ranking methods to adaptively sort results based on how 'relevant' they are for a specific query. The ranking SVM function uses a mapping function to describe the match between a search query and the features of each of the possible results.

  5. Regularization perspectives on support vector machines

    en.wikipedia.org/wiki/Regularization...

    Within mathematical analysis, Regularization perspectives on support-vector machines provide a way of interpreting support-vector machines (SVMs) in the context of other regularization-based machine-learning algorithms. SVM algorithms categorize binary data, with the goal of fitting the training set data in a way that minimizes the average of ...

  6. SVM - Wikipedia

    en.wikipedia.org/wiki/SVM

    Support vector machine, a machine learning algorithm; Stroboscopic effect visibility measure (SVM), a measure for assessing a type of temporal light artefacts;

  7. 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.

  8. Quoc V. Le - Wikipedia

    en.wikipedia.org/wiki/Quoc_V._Le

    Lê Viết Quốc (born 1982), [1] or in romanized form Quoc Viet Le, is a Vietnamese-American computer scientist and a machine learning pioneer at Google Brain, which he established with others from Google. He co-invented the doc2vec [2] and seq2seq [3] models in natural language processing.

  9. Category:Support vector machines - Wikipedia

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

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