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  2. Support vector machine - Wikipedia

    en.wikipedia.org/wiki/Support_vector_machine

    A training example of SVM with kernel given by φ((a, b)) = (a, b, a 2 + b 2) Suppose now that we would like to learn a nonlinear classification rule which corresponds to a linear classification rule for the transformed data points φ ( x i ) . {\displaystyle \varphi (\mathbf {x} _{i}).}

  3. Structured support vector machine - Wikipedia

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

    Whereas the SVM classifier supports binary classification, multiclass classification and regression, the structured SVM allows training of a classifier for general structured output labels. As an example, a sample instance might be a natural language sentence, and the output label is an annotated parse tree. Training a classifier consists of ...

  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. Supervised learning - Wikipedia

    en.wikipedia.org/wiki/Supervised_learning

    Active learning: Instead of assuming that all of the training examples are given at the start, active learning algorithms interactively collect new examples, typically by making queries to a human user. Often, the queries are based on unlabeled data, which is a scenario that combines semi-supervised learning with active learning.

  6. Sequential minimal optimization - Wikipedia

    en.wikipedia.org/wiki/Sequential_minimal...

    Sequential minimal optimization (SMO) is an algorithm for solving the quadratic programming (QP) problem that arises during the training of support-vector machines (SVM). It was invented by John Platt in 1998 at Microsoft Research. [1] SMO is widely used for training support vector machines and is implemented by the popular LIBSVM tool.

  7. Ranking SVM - Wikipedia

    en.wikipedia.org/wiki/Ranking_SVM

    In machine learning, a ranking SVM is a variant of the support vector machine algorithm, which is used to solve certain ranking problems (via learning to rank). The ranking SVM algorithm was published by Thorsten Joachims in 2002. [1] The original purpose of the algorithm was to improve the performance of an internet search engine.

  8. Keira Knightley Reveals the Unusual Reason She Doesn ... - AOL

    www.aol.com/lifestyle/keira-knightley-reveals...

    Keira Knightley’s number one reason for having no more kids isn’t the pain of childbirth or the endless nights of disrupted sleep. On Monday, Dec. 9. the actress, 39, gushed about her two ...

  9. List of psychological research methods - Wikipedia

    en.wikipedia.org/wiki/List_of_psychological...

    A wide range of research methods are used in psychology. These methods vary by the sources from which information is obtained, how that information is sampled, and the types of instruments that are used in data collection. Methods also vary by whether they collect qualitative data, quantitative data or both.