Matrix factorization - Matrix factorization expresses a matrix as a product of simpler matrices, either exactly or approximately.
Matrix norm - A matrix norm is a rule that assigns a nonnegative measure of size to a matrix, satisfying the usual norm properties: only the zero matrix has size zero...
Matrix normal distribution - The matrix normal distribution is a probability distribution for a matrix whose entries jointly follow a multivariate Gaussian distribution with a separable...
Matrix regularization - Matrix regularization is the use of penalties or constraints to control the structure of a matrix estimated from data.
Matrix semantics - Matrix semantics is the discipline of keeping track of what the rows, columns and cells of a data matrix mean: which axis is which entity, in which units...
Matrix sign function - The matrix sign function maps a square matrix's spectral components in the open right half of the complex plane to +1 and those in the open left half to −1.
Matrix variate Dirichlet distribution - A matrix variate Dirichlet distribution is a probability distribution for several random matrices that generalizes familiar scalar Dirichlet and matrix beta...
Matthews correlation coefficient - The Matthews correlation coefficient, or MCC, measures agreement between predicted and observed class labels using the full confusion matrix.
Matting Laplacian - The matting Laplacian is an image-dependent sparse matrix used in closed-form image matting.
Mauchly's sphericity test - Mauchly's sphericity test assesses a covariance assumption commonly used in univariate repeated-measures analysis of variance.
MAUVE (metric) - MAUVE is a measure for comparing two collections of generated and reference examples, developed for evaluating open-ended text generation.
Max error - Max error is the largest absolute difference between a prediction and its observed target in an evaluated dataset.
Max norm - The max norm of a finite-dimensional vector is the largest absolute value of any of its coordinates.
Max pooling - Max pooling replaces a neighborhood of values with its largest value.
Max-product algorithm - The max-product algorithm is a message-passing method for finding a highest-probability joint assignment in a factorized probability model.
Maxim, Gricean - A Gricean maxim is a conversational expectation used in H. P. Grice's account of how people interpret what others communicate beyond literal wording.
Maximal entropy random walk - A maximal entropy random walk is a graph-based Markov process whose transition probabilities maximize the long-run entropy rate of allowed paths.
Maximal independent set - A maximal independent set is a set of graph nodes with no edges between selected nodes, to which no additional node can be added without creating an edge...
Maximin - Maximin is a decision rule that chooses the option with the best worst-case payoff.
Maximin equilibrium - In the standard two-player zero-sum setting, a maximin equilibrium is a pair of strategies in which each player secures the best worst-case expected payoff...
Maximum a posteriori - Maximum a posteriori, usually abbreviated MAP, selects a value or hypothesis that maximizes its posterior probability after evidence is observed.
Maximum a posteriori policy optimization - Maximum a posteriori policy optimization, usually called MPO, is a reinforcement-learning method that improves a policy through alternating action...
Maximum entropy - Maximum entropy is a principle for choosing a probability distribution that has the greatest entropy among distributions satisfying specified constraints.
Maximum-entropy Markov model - A maximum-entropy Markov model, or MEMM, is a conditional sequence-labeling model that uses a log-linear classifier to predict each label from the preceding...
Maximum entropy reinforcement learning - Maximum entropy reinforcement learning trains a policy to maximize a combination of expected reward and policy entropy.
Maximum entropy spectral estimation - Maximum entropy spectral estimation estimates how a stationary time series distributes power across frequencies by choosing a spectrum with maximum entropy...
Maximum expected utility - Maximum expected utility, or MEU, is the principle of choosing the available action or policy with the highest probability-weighted utility across its...
Maximum Flow - Maximum flow is the largest feasible amount of a single commodity that can move from a designated source to a designated sink through a capacitated network.
Maximum inner-product search - Maximum inner-product search is the task of finding the stored vector with the largest dot product with a query vector.
Maximum likelihood estimate - A maximum likelihood estimate is a parameter value, or set of values, that maximizes the likelihood of the observed data within a specified statistical model.
Maximum margin separator - A maximum margin separator is a decision boundary that separates labeled classes while maximizing its distance from the nearest training examples.
Maximum pseudolikelihood estimation - Maximum pseudolikelihood estimation fits model parameters by maximizing a product of conditional probabilities, often one variable conditional on all the...
Maximum spanning tree - A maximum spanning tree is a tree that connects every vertex of a weighted graph while maximizing the sum of its selected edge weights.
Maze / labyrinth artifacts - Maze or labyrinth artifacts are spurious, maze-like patterns that can appear in reconstructed digital images, particularly after demosaicking raw sensor data.
MCA - MCA means measurement capability assessment, also called measurement capability analysis, in the supplied NIST statistical glossary.
MCS algorithm - The MCS algorithm, in mathematical optimization, is Multilevel Coordinate Search: a method for minimizing a function subject to coordinate bounds using...
Mean - The mean, usually meaning the arithmetic mean, is the sum of a set of numerical values divided by the number of values.
Mean absolute deviation (m.a.d.) - Mean absolute deviation is the average absolute distance of observations from a specified center.
Mean Absolute Error - Mean Absolute Error, or MAE, is the arithmetic mean of the absolute differences between predictions and their corresponding observed or reference values.
Mean absolute percentage error - Mean absolute percentage error, or MAPE, averages the absolute prediction error relative to each observation's actual value.
Mean average precision - Mean average precision, often written MAP or mAP, is an average of average-precision scores over evaluation units such as search queries or object categories.
Mean directional accuracy - Mean directional accuracy, or MDA, is the proportion of evaluated forecasts that correctly predict the direction of a specified change.
Mean field approximation - Mean field approximation simplifies a system of interacting variables by representing their combined behavior through separate factors and average effects.
Mean opinion score - A mean opinion score, or MOS, is an average of ratings assigned on a predefined opinion scale in a quality-evaluation study.
Mean Percentage Error - Mean Percentage Error, or MPE, is the arithmetic average of signed forecast errors expressed as percentages of the corresponding actual values.
Mean pooling - Mean pooling is an operation that combines a collection of equally sized vectors by averaging their corresponding coordinates.