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  2. Generalization (learning) - Wikipedia

    en.wikipedia.org/wiki/Generalization_(learning)

    Generalization is the concept that humans, other animals, and artificial neural networks use past learning in present situations of learning if the conditions in the situations are regarded as similar. [1] The learner uses generalized patterns, principles, and other similarities between past experiences and novel experiences to more efficiently ...

  3. Concept learning - Wikipedia

    en.wikipedia.org/wiki/Concept_learning

    Concept learning, also known as category learning, concept attainment, and concept formation, is defined by Bruner, Goodnow, & Austin (1956) as "the search for and testing of attributes that can be used to distinguish exemplars from non exemplars of various categories". [a] More simply put, concepts are the mental categories that help us ...

  4. Vapnik–Chervonenkis theory - Wikipedia

    en.wikipedia.org/wiki/Vapnik–Chervonenkis_theory

    Machine learningand data mining. Vapnik–Chervonenkis theory (also known as VC theory) was developed during 1960–1990 by Vladimir Vapnik and Alexey Chervonenkis. The theory is a form of computational learning theory, which attempts to explain the learning process from a statistical point of view.

  5. Universal law of generalization - Wikipedia

    en.wikipedia.org/.../Universal_law_of_generalization

    The universal law of generalization is a theory of cognition stating that the probability of a response to one stimulus being generalized to another is a function of the “distance” between the two stimuli in a psychological space. It was introduced in 1987 by Roger N. Shepard, [1] [2] who began researching mechanisms of generalization while ...

  6. Neural network (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Neural_network_(machine...

    e. In machine learning, a neural network (also artificial neural network or neural net, abbreviated ANN or NN) is a model inspired by the structure and function of biological neural networks in animal brains. [ 1 ][ 2 ] An ANN consists of connected units or nodes called artificial neurons, which loosely model the neurons in the brain.

  7. Statistical learning theory - Wikipedia

    en.wikipedia.org/wiki/Statistical_learning_theory

    Statistical learning theory is a framework for machine learning drawing from the fields of statistics and functional analysis. [1][2][3] Statistical learning theory deals with the statistical inference problem of finding a predictive function based on data. Statistical learning theory has led to successful applications in fields such as ...

  8. Domain-general learning - Wikipedia

    en.wikipedia.org/wiki/Domain-general_learning

    Domain-general learning. Domain-general learning theories of development suggest that humans are born with mechanisms in the brain that exist to support and guide learning on a broad level, regardless of the type of information being learned. [1][2][3] Domain-general learning theories also recognize that although learning different types of new ...

  9. Roger Shepard - Wikipedia

    en.wikipedia.org/wiki/Roger_Shepard

    Roger Shepard. Roger Newland Shepard (January 30, 1929 – May 30, 2022 [1]) was an American cognitive scientist and author of the "universal law of generalization" (1987). He was considered a father of research on spatial relations. He studied mental rotation, and was an inventor of non-metric multidimensional scaling, a method for ...