Co-domain - The co-domain of a function is the declared set in which its output values lie. If a function is written f:U→V, U is its domain and V is its co-domain.
Coefficient matrix - A coefficient matrix is the rectangular array of numbers multiplying the variables in a system of linear equations.
Coefficient of determination - The coefficient of determination, usually written R², compares a regression model's squared prediction errors with the squared deviations of the observed...
Column space - The column space of a matrix is the set of all linear combinations of its columns.
Communication-avoiding algorithm - A communication-avoiding algorithm reorganizes computation to reduce costly data movement or communication events.
Communication network - A communication network is a collection of devices connected by links that allow them to exchange information.
Commutation matrix - A commutation matrix is a permutation matrix that rearranges a vectorized matrix into the vectorized form of its transpose.
Compact quasi-Newton representation - A compact quasi-Newton representation expresses a curvature-approximation matrix as a simple starting matrix plus a correction assembled from a small...
Concentration inequality - A concentration inequality bounds the probability that a random quantity differs substantially from a reference value, commonly its expectation.
Condition number - A condition number measures how sensitive a mathematical problem's solution can be to changes in its input.
Conditional entropy - Conditional entropy measures the average uncertainty remaining about one random variable after another is known.
Conditional expectation - Conditional expectation is the average value of a random quantity given specified information.
Conjugate gradient - Conjugate gradient is an iterative method for solving a linear system Ax = b when A is symmetric positive definite in the real-valued setting.
Conjugate prior - A conjugate prior is a prior probability distribution whose posterior stays within the same distribution family after updating with a specified likelihood.
Conjugate transpose - The conjugate transpose of a matrix is obtained by exchanging its rows and columns and taking the complex conjugate of every entry.
Consensus based optimization - Consensus based optimization is a derivative-free population method that moves candidate solutions toward an objective-weighted consensus location while...
Constrained minimization - Constrained minimization is the task of finding the smallest value of an objective function while satisfying specified restrictions on the decision variables.
Constrained optimization - Constrained optimization seeks the best value of an objective while restricting decisions to an allowed set.
Constrained optimization problem - A constrained optimization problem, abbreviated COP in the supplied AIMA glossary, extends a constraint satisfaction problem with preferences.
Contingency Matrix - A contingency matrix is a table of counts showing how two labelings overlap on the same collection of items.
Continuity in probability - Continuity in probability is a property of a stochastic process: as an index approaches a fixed index, the corresponding random variables approach each...
Continuous optimization - Continuous optimization is the study of choosing real-valued decision variables to minimize or maximize an objective, subject to any constraints.
Contractive operator - A contractive operator is a mapping that reduces distances by a uniform factor smaller than one.
Convex function - A convex function is a function on a convex domain whose value at any weighted average of two inputs is no greater than the corresponding weighted average...
Convex optimization - Convex optimization is the minimization of a convex objective over a convex feasible set. Its defining advantage is that every local optimum is also global.
Convex optimization problem - A convex optimization problem is a mathematical specification that asks for the minimum of a convex objective over a convex set of allowed decisions.
Convex set - A convex set contains the entire straight line segment joining any two of its points.
Coreset - A coreset is a compact representation of a dataset designed to preserve specified properties relevant to a particular task.
Criss-cross algorithm - The criss-cross algorithm is a family of pivot methods for linear programming that can start from a basis without requiring primal or dual feasibility.
Cross-sectional data - Cross-sectional data describe multiple units, such as people, businesses or images, through observations treated as a single snapshot rather than as...
Crout matrix decomposition - Crout matrix decomposition is an LU factorization convention in which a matrix is expressed as a lower-triangular factor L times an upper-triangular factor...
CUR matrix approximation - CUR matrix approximation represents a data matrix using selected columns C, selected rows R and a connecting matrix U, so that A is approximately CUR.
Cutting-plane method - A cutting-plane method progressively narrows an optimization search by adding valid linear inequalities called cuts.
Damerau - Levenshtein distance - Damerau - Levenshtein distance measures the smallest number of edits needed to transform one string into another when the permitted unit-cost operations are...
Data Imputation - Data imputation replaces missing values with estimates or specified substitutes so that incomplete records can be used in an analysis or machine-learning...
Data matrix - A data matrix is a rectangular arrangement of data values used for analysis or learning.
De Boor's algorithm - De Boor's algorithm evaluates a B-spline curve at a specified parameter value through repeated weighted combinations of nearby control points.
De Casteljau's algorithm - De Casteljau's algorithm evaluates a Bézier curve by repeatedly interpolating between neighboring control points.
Decision region - A decision region is the set of inputs that a classifier assigns to a particular output label.
Deduction theorem - The deduction theorem connects reasoning from an assumption with reasoning about an implication.
Defective matrix - A defective matrix is a square matrix that lacks enough linearly independent eigenvectors to form a basis.
Degree of belonging - A degree of belonging is a numerical value expressing how strongly a data point is associated with a cluster under a specified clustering method.
Derivative-free optimization - Derivative-free optimization searches for good decision-variable values without requiring derivatives of the objective or constraints to be supplied.
Determinant - The determinant is a scalar associated with a square matrix.
Deterministic global optimization - Deterministic global optimization uses systematic mathematical procedures to seek a globally best feasible solution and establish an optimality guarantee...
Diagnosis - In this machine-learning context, diagnosis means investigating a trained model's performance by comparing training error, validation error and baselines.
Directed cycle - A directed cycle is a sequence of directed edges that follows their arrow directions and returns to its starting vertex.