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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. List of typographical symbols and punctuation marks

    en.wikipedia.org/wiki/List_of_typographical...

    Typographical symbols and punctuation marks are marks and symbols used in typography with a variety of purposes such as to help with legibility and accessibility, or to identify special cases. This list gives those most commonly encountered with Latin script. For a far more comprehensive list of symbols and signs, see List of Unicode characters.

  7. Perceptron - Wikipedia

    en.wikipedia.org/wiki/Perceptron

    In machine learning, the perceptron (or McCulloch–Pitts neuron) is an algorithm for supervised learning of binary classifiers.A binary classifier is a function which can decide whether or not an input, represented by a vector of numbers, belongs to some specific class. [1]

  8. 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.

  9. Mathematical psychology - Wikipedia

    en.wikipedia.org/wiki/Mathematical_psychology

    Mathematical psychology is an approach to psychological research that is based on mathematical modeling of perceptual, thought, cognitive and motor processes, and on the establishment of law-like rules that relate quantifiable stimulus characteristics with quantifiable behavior (in practice often constituted by task performance).