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learning by generalization

См. также в других словарях:

  • Generalization error — The generalization error of a machine learning model is a function that measures how far the student machine is from the teacher machine in average over the entire set of possible data that can be generated by the teacher after each iteration of… …   Wikipedia

  • generalization — /jen euhr euh leuh zay sheuhn/, n. 1. the act or process of generalizing. 2. a result of this process; a general statement, idea, or principle. 3. Logic. a. a proposition asserting something to be true either of all members of a certain class or… …   Universalium

  • Eager learning — In artificial intelligence, eager learning is a learning method in which the system tries to construct a general, input independent target function during training of the system, as opposed to lazy learning, where generalization beyond the… …   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

  • psychomotor learning — Introduction       development of organized patterns of muscular activities guided by signals from the environment. Behavioral examples include driving a car and eye hand coordination tasks such as sewing, throwing a ball, typing, operating a… …   Universalium

  • Probably approximately correct learning — In computational learning theory, probably approximately correct learning (PAC learning) is a framework for mathematical analysis of machine learning. It was proposed in 1984 by Leslie Valiant.[1] In this framework, the learner receives samples… …   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

  • One-shot learning — is an object categorization problem of current research interest in computer vision. Whereas most machine learning based object categorization algorithms require training on hundreds or thousands of images and very large datasets, one shot… …   Wikipedia

  • Instance-based learning — In machine learning, instance based learning or memory based learning is a family of learning algorithms that, instead of performing explicit generalization, compare new problem instances with instances seen in training, which have been stored in …   Wikipedia

  • Lazy learning — In artificial intelligence, lazy learning is a learning method in which generalization beyond the training data is delayed until a query is made to the system, as opposed to in eager learning, where the system tries to generalize the training… …   Wikipedia

  • Multilinear subspace learning — (MSL) aims to learn a specific small part of a large space of multidimensional objects having a particular desired property. It is a dimensionality reduction approach for finding a low dimensional representation with certain preferred… …   Wikipedia

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