approximate algorithm

приближенный алгоритм

Англо-русский словарь по компьютерной безопасности. . 2011.

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  • Algorithm — Flow chart of an algorithm (Euclid s algorithm) for calculating the greatest common divisor (g.c.d.) of two numbers a and b in locations named A and B. The algorithm proceeds by successive subtractions in two loops: IF the test B ≤ A yields yes… …   Wikipedia

  • Approximate string matching — In computing, approximate string matching is the technique of finding approximate matches to a pattern in a string. The closeness of a match is measured in terms of the number of primitive operations necessary to convert the string into an exact… …   Wikipedia

  • k-nearest neighbor algorithm — KNN redirects here. For other uses, see KNN (disambiguation). In pattern recognition, the k nearest neighbor algorithm (k NN) is a method for classifying objects based on closest training examples in the feature space. k NN is a type of instance… …   Wikipedia

  • Great Deluge algorithm — The Great Deluge algorithm (GD) is a generic algorithm applied to optimization problems. It is similar in many ways to the hill climbing and simulated annealing algorithms.The name comes from the analogy that in a great deluge a person climbing a …   Wikipedia

  • Constraint algorithm — In mechanics, a constraint algorithm is a method for satisfying constraints for bodies that obey Newton s equations of motion. There are three basic approaches to satisfying such constraints: choosing novel unconstrained coordinates ( internal… …   Wikipedia

  • Metropolis–Hastings algorithm — The Proposal distribution Q proposes the next point that the random walk might move to. In mathematics and physics, the Metropolis–Hastings algorithm is a Markov chain Monte Carlo method for obtaining a sequence of random samples from a… …   Wikipedia

  • Lanczos algorithm — The Lanczos algorithm is an iterative algorithm invented by Cornelius Lanczos that is an adaptation of power methods to find eigenvalues and eigenvectors of a square matrix or the singular value decomposition of a rectangular matrix. It is… …   Wikipedia

  • Approximation algorithm — In computer science and operations research, approximation algorithms are algorithms used to find approximate solutions to optimization problems. Approximation algorithms are often associated with NP hard problems; since it is unlikely that there …   Wikipedia

  • Nested sampling algorithm — The nested sampling algorithm is a computational approach to the problem of comparing models in Bayesian statistics, developed in 2004 by physicist John Skilling.[1] Contents 1 Background 2 Applications 3 …   Wikipedia

  • Genetic algorithm — A genetic algorithm (GA) is a search heuristic that mimics the process of natural evolution. This heuristic is routinely used to generate useful solutions to optimization and search problems. Genetic algorithms belong to the larger class of… …   Wikipedia

  • Expectation-maximization algorithm — An expectation maximization (EM) algorithm is used in statistics for finding maximum likelihood estimates of parameters in probabilistic models, where the model depends on unobserved latent variables. EM alternates between performing an… …   Wikipedia

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