Confounded - Variables or effects are confounded when their contributions cannot be distinguished adequately in the comparison or design being used.
Confounder - A confounder is a variable that, in the relevant causal structure, helps create a noncausal association between an exposure or intervention and an outcome.
Confounding - Confounding is a source of bias that can distort the interpretation of an observed association as a causal effect.
Confusion matrix - A confusion matrix is a table that lays a classifier's predictions against the true classes, showing not just how often it is right but exactly which...
Conjoint analysis - Conjoint analysis is a family of methods for studying how people evaluate alternatives described by several attributes.
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.
Conjunct ordering - Conjunct ordering is the choice of the sequence in which a reasoning or query system evaluates conditions joined by logical AND.
Conjunction - Conjunction is the logical operation AND. A conjunction is true exactly when every component statement, called a conjunct, is true.
Conjunctive normal form - Conjunctive normal form, or CNF, is a way of writing a logical formula as an AND of clauses, where each clause is an OR of literals.
Connected-component labeling - Connected-component labeling assigns a distinct label to each connected group of foreground pixels in an image.
Connection string - A connection string is a structured text value that tells a software component how to connect to a data source or service.
Connectionist expert system - A connectionist expert system uses a neural-style network to represent and apply knowledge for a specialized task.
Connectionist temporal classification - Connectionist temporal classification, or CTC, is a training method for sequence models that learn from unaligned data, where the input and output sequences...
Connotation frame - A connotation frame is a structured representation of the attitudes and other implications a predicate can convey about its participants.
Connotations - Connotations are the associations, evaluations or emotional overtones carried by a word or expression beyond its basic descriptive meaning.
Consensus based optimization - Consensus based optimization is a derivative-free population method that moves candidate solutions toward an objective-weighted consensus location while...
Consensus clustering - Consensus clustering combines information from several clustering results to identify patterns of agreement.
Consensus dynamics - Consensus dynamics studies how interacting agents change their states over time to reach agreement on a quantity.
Consent - Consent is a person's agreement to a specified activity or use of information, given under conditions that make the agreement meaningful.
Conservative approximation - A conservative approximation simplifies a representation while preserving a direction of correctness.
Conservative policy iteration - Conservative policy iteration is a reinforcement-learning approach that improves a policy by mixing it with a candidate improvement instead of replacing it...
Conservative Q-learning - Conservative Q-learning (CQL) is an offline reinforcement-learning framework that discourages inflated action-value estimates when learning from a fixed...
Conservative vector field - A conservative vector field is a vector field that can be expressed as the gradient of a scalar potential on its domain.
Consistency - Consistency means satisfying the compatibility requirements of a specified formal setting.
Consistency regularization - Consistency regularization is a training principle for semi-supervised learning: a model's prediction for an example should stay the same when that example...
Consistent estimator - A consistent estimator is an estimation rule whose output converges in probability to the quantity being estimated as the sample size grows, under stated...
Consonant - A consonant is a speech sound typically produced with a narrowing or closure somewhere in the vocal tract.
Constant bitrate - Constant bitrate, or CBR, is a coding or delivery mode designed to maintain a specified bit consumption or output rate over the relevant interval and buffer...
Constative speech act - A constative speech act presents something as being the case, committing the speaker to a proposition in the relevant conversational sense.
Constellation model - A constellation model is a probabilistic, part-based model for recognizing object categories in images.
Constituency - Constituency is the organization of a sentence into groups of words that function as grammatical units.
Constituency parsing - Constituency parsing is the analysis of a sentence's grammatical structure as a tree of nested phrases, such as noun phrases and verb phrases, showing how...
Constitutional AI - Constitutional AI is an approach to shaping AI behavior through an explicit set of written principles used in training and feedback.
Constrained clustering - Constrained clustering forms groups while taking additional requirements or background knowledge into account.
Constrained Hidden Markov Model - A constrained hidden Markov model is a hidden Markov model with extra rules limiting which states or transitions are allowed, so the model can only produce...
Constrained least squares - Constrained least squares finds model parameters that minimize a sum of squared residuals while obeying specified restrictions.
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 mixture model - A constrained mixture model is a mixture model whose components are tied by extra rules, such as shared shapes or linked centers, so the mixture fits...
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.
Constraint Grammar - Constraint Grammar is a rule-based framework for analyzing text by using contextual constraints to remove or select among possible linguistic readings.
Constraint graph - A constraint graph represents the structure of a binary constraint-satisfaction problem.
Constraint hypergraph - A constraint hypergraph represents a constraint-satisfaction problem whose constraints may involve more than two variables.
Constraint learning - Constraint learning records new restrictions derived from failures encountered while solving a constraint problem.
Constraint logic programming - Constraint logic programming, or CLP, combines logic programming with specialized constraint solving.
Constraint propagation - Constraint propagation uses known restrictions to derive further restrictions on variable values.