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Johnson's algorithm — is a way to find shortest paths between all pairs of vertices in a sparse directed graph. It allows some of the edge weights to be negative numbers, but no negative weight cycles may exist.Algorithm descriptionJohnson s algorithm consists of the… … Wikipedia
Linear regression — Example of simple linear regression, which has one independent variable In statistics, linear regression is an approach to modeling the relationship between a scalar variable y and one or more explanatory variables denoted X. The case of one… … Wikipedia
Linear least squares (mathematics) — This article is about the mathematics that underlie curve fitting using linear least squares. For statistical regression analysis using least squares, see linear regression. For linear regression on a single variable, see simple linear regression … Wikipedia
Minimum wage — A minimum wage is the lowest hourly, daily or monthly remuneration that employers may legally pay to workers. Equivalently, it is the lowest wage at which workers may sell their labour. Although minimum wage laws are in effect in a great many… … Wikipedia
Least squares — The method of least squares is a standard approach to the approximate solution of overdetermined systems, i.e., sets of equations in which there are more equations than unknowns. Least squares means that the overall solution minimizes the sum of… … Wikipedia
Boosting — is a machine learning meta algorithm for performing supervised learning. Boosting is based on the question posed by KearnsMichael Kearns. Thoughts on hypothesis boosting. Unpublished manuscript. 1988] : can a set of weak learners create a single… … Wikipedia
Minimum message length — (MML) is a formal information theory restatement of Occam s Razor: even when models are not equal in goodness of fit accuracy to the observed data, the one generating the shortest overall message is more likely to be correct (where the message… … Wikipedia
Minimum description length — The minimum description length (MDL) principle is a formalization of Occam s Razor in which the best hypothesis for a given set of data is the one that leads to the best compression of the data. MDL was introduced by Jorma Rissanen in 1978. It is … Wikipedia
Deviance (statistics) — In statistics, deviance is a quality of fit statistic for a model that is often used for statistical hypothesis testing. The deviance for a model M0 is defined as Here denotes the fitted values of the parameters in the model M0, while denotes the … Wikipedia
Errors and residuals in statistics — For other senses of the word residual , see Residual. In statistics and optimization, statistical errors and residuals are two closely related and easily confused measures of the deviation of a sample from its theoretical value . The error of a… … Wikipedia
