Domain Constraint - A domain constraint restricts which values are valid for an attribute or type.
Domain driven data mining - Domain driven data mining is an approach to discovering useful patterns that incorporates the knowledge, objectives, constraints, and working practices of...
Domain elements - Domain elements are the objects that belong to the domain of a logical model. They are what variables range over and what names or other terms can refer to.
Domain generalization - Domain generalization is the task of learning from available environments so that a model works well in a new environment whose data were not used to train...
Domain shift - Domain shift is a change in the data conditions between the setting where an AI model was developed or evaluated and another setting where it is used.
Domain (spatial) operation - In the supplied computational-photography glossary, a domain (spatial) operation changes where image information is sampled: an output pixel obtains its...
Dominance-based rough set approach - The dominance-based rough set approach, or DRSA, analyses decisions involving ordered criteria and ordered outcome classes.
Dominant resource fairness - Dominant resource fairness, or DRF, is a resource-allocation rule that extends max-min fairness to several resource types.
Dominant strategy - A dominant strategy is a strategy that gives a player an outcome at least as good as every alternative, whatever strategies the other players choose, under...
Dominant strategy equilibrium - A dominant strategy equilibrium is a joint choice of strategies in which every player uses a dominant strategy.
Dominating policy - A dominating policy, in the Markov decision-process sense used here, is a policy whose expected return is at least as high as that of every alternative...
Donor (imputation) - A donor in imputation is a record that supplies values used to replace missing or inconsistent values in another record, called the recipient.
DOPIPE - DOPIPE is a form of loop-level parallelism that divides work from a loop into cooperating pipeline stages.
Dormand - Prince method - The Dormand - Prince method is an explicit Runge - Kutta method for numerically solving ordinary differential equations with initial values.
Dot plot - A dot plot, in the distribution-display sense used by the source glossary, represents observations as dots positioned along a measurement axis, with...
Dot product - The dot product of two real-valued vectors is the sum of the products of their corresponding components.
Dot-product attention - Dot-product attention is a mechanism that scores the compatibility of a query vector with key vectors using their dot products, converts those scores into...
Double deep Q-network - A double deep Q-network, usually called Double DQN, is a reinforcement-learning method that separates choosing a promising next action from estimating that...
Double delta feature - A double delta feature is the change of a change: it measures how quickly a measurement is speeding up or slowing down, rather than how fast it is simply...
Double hashing - Double hashing is an open-addressing method for resolving collisions in a hash table.
Double machine learning - Double machine learning (DML), also called double/debiased machine learning, is a framework for estimating a target statistical or causal parameter while...
Double mass analysis - Double mass analysis compares the cumulative totals of two related data series to examine whether their relationship remains consistent over time.
Double moving average - A double moving average is a moving average applied to a series that has already been smoothed by a moving average.
Double Q-learning - Double Q-learning is an off-policy reinforcement-learning method that uses two action-value estimates to separate choosing a promising next action from...
Double sampling - Double sampling, in the OECD glossary's principal industrial-inspection sense, is an acceptance-sampling plan that permits a decision after a first sample...
Double-sampling problem in Bellman-error minimization - The double-sampling problem in Bellman-error minimization is the difficulty of obtaining an unbiased gradient estimate when that gradient contains a product...
Double-spending - Double-spending is an attempt or failure in which the same digital asset or spendable value is used more than once in conflicting transactions.
Doubly block circulant - Doubly block circulant describes a matrix built from a circulant arrangement of blocks, with each block itself circulant.
Doubly robust off-policy evaluation - Doubly robust off-policy evaluation estimates the expected reward of a target decision policy from data collected by another policy, combining a reward or...
Downhill simplex - Downhill simplex is a derivative-free optimization method commonly referring to the Nelder - Mead algorithm.
Downward refinement property - The downward refinement property is a property of a planning abstraction hierarchy that allows abstract solutions to be refined into concrete solutions...
Doxing - Doxing, also spelled doxxing, is the deliberate online exposure of someone's identity or personal information without their consent, typically to enable...
DPLL algorithm - The DPLL algorithm is a complete search procedure for deciding whether a propositional-logic formula in conjunctive normal form can be satisfied.
Drift (tracking) - Tracking drift is the progressive departure of a visual tracker's estimated target location or representation from the intended target.
Dropout - Dropout is a neural-network regularization technique that randomly suppresses selected activations during training.
Dropping conditions - Dropping conditions is a generalization operation in rule or concept learning that removes one or more requirements from a conjunctive description.
Dual extended Kalman filter - A dual extended Kalman filter (dual EKF or DEKF) uses two coupled estimation processes to track both a system's changing hidden state and uncertain model...
Dual graph - In constraint satisfaction, a dual graph represents each original constraint as a node and connects two nodes when their constraints share one or more...
Dual norm - The dual norm associated with a norm measures the largest inner product a vector can achieve against any vector in that norm's unit ball.
Dual problem - A dual problem is an optimization problem constructed from another problem, called the primal, to obtain bounds on its best objective value.
Dual total correlation - Dual total correlation (DTC) is an information-theoretic measure of dependence among several random variables.
DualDICE - DualDICE is a reinforcement-learning method for estimating corrections between a target policy's discounted state-action distribution and the distribution...
Duality gap - The duality gap is the difference between the optimal values of a primal optimization problem and its associated dual.
Dueling bandit - A dueling bandit is a sequential learning problem in which the learner chooses pairs of options and receives relative feedback, such as which option was...
Dueling deep Q-network - A dueling deep Q-network is a Q-value network architecture that combines a shared state representation with two output streams: a scalar value stream and an...
Dummy variable - A dummy variable is a numerical indicator, usually coded 1 when a specified condition or category applies and 0 otherwise.
Duncan's new multiple range test - Duncan's new multiple range test is a procedure for comparing ordered group means using a sequence of studentized-range comparisons.
Dunn-Sidák test - The Dunn-Sidák test is a multiple-testing adjustment that assigns a smaller significance threshold to each test in a specified family.