Statistical learning theory

Statistical learning theory

Statistical learning theory is an ambiguous term.

#It may refer to computational learning theory, which is a sub-field of theoretical computer science that studies how algorithms can learn from data.
#It may refer to Vapnik-Chervonenkis theory, which is a specific approach to computational learning theory, proposed by Vladimir Vapnik and Alexey Chervonenkis.


Wikimedia Foundation. 2010.

Игры ⚽ Нужно сделать НИР?

Look at other dictionaries:

  • learning theory — ▪ psychology Introduction       any of the proposals put forth to explain changes in behaviour produced by practice, as opposed to other factors, e.g., physiological development.       A common goal in defining any psychological (psychology)… …   Universalium

  • Computational learning theory — In theoretical computer science, computational learning theory is a mathematical field related to the analysis of machine learning algorithms. Contents 1 Overview 2 See also 3 References 3.1 Surveys …   Wikipedia

  • 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.VC theory… …   Wikipedia

  • Concept learning — Concept learning, also known as category learning, concept attainment, and concept formation, is largely based on the works of the cognitive psychologist Jerome Bruner. Bruner, Goodnow, Austin (1967) defined concept attainment (or concept… …   Wikipedia

  • Machine learning — is a subfield of artificial intelligence that is concerned with the design and development of algorithms and techniques that allow computers to learn . In general, there are two types of learning: inductive, and deductive. Inductive machine… …   Wikipedia

  • Statistical semantics — is the study of how the statistical patterns of human word usage can be used to figure out what people mean, at least to a level sufficient for information access (Furnas, 2006). How can we figure out what words mean, simply by looking at… …   Wikipedia

  • Supervised learning — is a machine learning technique for learning a function from training data. The training data consist of pairs of input objects (typically vectors), and desired outputs. The output of the functioncan be a continuous value (called regression), or… …   Wikipedia

  • Transduction (machine learning) — In logic, statistical inference, and supervised learning,transduction or transductive inference is reasoning fromobserved, specific (training) cases to specific (test) cases. In contrast, induction is reasoning from observed training casesto… …   Wikipedia

  • Theory of conjoint measurement — The theory of conjoint measurement (also known as conjoint measurement or additive conjoint measurement) is a general, formal theory of continuous quantity. It was independently discovered by the French economist Gerard Debreu (1960) and by the… …   Wikipedia

  • animal learning — ▪ zoology Introduction       the alternation of behaviour as a result of individual experience. When an organism can perceive and change its behaviour, it is said to learn.       That animals can learn seems to go without saying. The cat that… …   Universalium

Share the article and excerpts

Direct link
Do a right-click on the link above
and select “Copy Link”