- probability learning
- вероятностное обучение
Англо-русский словарь по исследованиям и ноу-хау. Е.Г. Коваленк. 2015.
probability learning
Смотреть что такое "probability learning" в других словарях:
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
probability theory — Math., Statistics. the theory of analyzing and making statements concerning the probability of the occurrence of uncertain events. Cf. probability (def. 4). [1830 40] * * * Branch of mathematics that deals with analysis of random events.… … Universalium
Learning — Learn and Learned redirect here. For other uses, see Learn (disambiguation) and Learned (disambiguation). Neuropsychology Topics … Wikipedia
Learning classifier system — A learning classifier system, or LCS, is a machine learning system with close links to reinforcement learning and genetic algorithms. First described by John Holland, his LCS consisted of a population of binary rules on which a genetic algorithm… … 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
Bayesian probability — Bayesian statistics Theory Bayesian probability Probability interpretations Bayes theorem Bayes rule · Bayes factor Bayesian inference Bayesian network Prior · Posterior · Likelihood … Wikipedia
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
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
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
Decision tree learning — This article is about decision trees in machine learning. For the use of the term in decision analysis, see Decision tree. Decision tree learning, used in statistics, data mining and machine learning, uses a decision tree as a predictive model… … Wikipedia
