Reference class problem - The reference class problem is the difficulty of deciding which group of comparable cases should inform a probability judgment about a particular case.
Reference controller - A reference controller, in the robotics tracking sense used here, is a controller designed to make a system follow a specified reference path or trajectory.
Reference counts - In memory-bounded search, reference counts can track how many possible arrivals at a state have already occurred.
Reference group - A reference group is a group of observations, or a defined group that could be observed, used as a point of comparison in a study.
Reference metadata - Reference metadata describe the content, methods and quality of statistical data so that users can interpret and assess them.
Reference path - A reference path is a specified geometric route that a moving system is intended to follow.
Reference point - A reference point is a temporal anchor used to interpret when an event occurs relative to a viewpoint in a sentence or discourse.
Reference prior - A reference prior is a prior distribution constructed by a formal information-based procedure to provide a baseline Bayesian analysis for a specified...
Reference text - Reference text is a prepared example of an appropriate response used when evaluating generated text.
Referent - A referent is the person, object, event, or other entity that someone refers to through an expression in context.
Referential Constraint - A referential constraint is an integrity rule requiring a reference in one record to correspond to an eligible referenced record.
Referential density - Referential density is the degree to which participants in discourse are expressed overtly rather than left unexpressed and recovered from context.
Referential integrity - Referential integrity is the condition in which references between database records satisfy their declared rules.
Referential transparency - Referential transparency concerns whether an expression can be replaced by an equivalent expression or value without changing the meaning or relevant...
Referring expression generation - Referring expression generation is the task of producing language that helps a listener or reader identify an intended entity.
Reflection - Reflection is a workflow strategy in which an AI system examines an earlier output or action result before deciding what to do next.
Reflection removal - Reflection removal is the process of estimating and reducing an unwanted reflected image component, commonly in photographs taken through glass.
Reflective architecture - A reflective architecture is a system design that supports computation about the system's own structure, state, or ongoing computation.
Reflexive Rule - The reflexive rule for functional dependencies states that an attribute set determines each of its subsets. If Y is a subset of X, then X → Y.
Reformulation - Reformulation is expressing an earlier message again in a different form.
Refutation - Refutation is a method of reasoning that establishes a contradiction from a set of assumptions.
Region Based Convolutional Neural Networks - Region-based convolutional neural networks are object-detection approaches that analyze candidate image regions using convolutional features to identify...
Region connection calculus - Region connection calculus (RCC) is a formal approach to qualitative spatial reasoning that describes relationships between regions, such as separation...
Region growing - Region growing is a segmentation approach that starts from one or more seed locations and expands regions by adding neighboring elements that satisfy a...
Region of interest - A region of interest, or ROI, is a selected part of an image, video frame or other dataset that receives particular attention or processing.
Regions - Regions, in computer vision, are groups of image locations treated as meaningful units for analysis.
Regression Analysis - Regression analysis is a family of statistical methods for studying how an outcome is related to one or more predictors.
Regression coefficients - Regression coefficients are numerical parameters that determine how predictors enter a regression model.
Regression equation - A regression equation is a mathematical expression describing how an outcome, or a chosen conditional summary of that outcome, depends on predictors in a...
Regression fallacy - The regression fallacy is the mistake of attributing a change after an unusually high or low observation entirely to an intervention while overlooking...
Regression line - A regression line is a straight-line representation of a modeled relationship between a numerical outcome and a predictor.
Regression model - A regression model represents a relationship between predictors and an outcome, commonly for predicting a numerical quantity or describing a conditional...
Regression planning - Regression planning is a planning method that searches backward from a desired goal to the conditions needed before earlier actions.
Regression spline - A regression spline models a relationship using polynomial pieces joined at specified locations called knots.
Regression surface - A regression surface represents a fitted relationship between an outcome and two or more predictors.
Regression to the mean - Regression to the mean is the tendency for observations selected because they are unusually high or low to be followed, on average, by less extreme...
Regression tree - A regression tree is a tree-structured predictive model for a numerical outcome.
Regression with ARIMA errors - Regression with ARIMA errors is a forecasting model that combines a regression relationship with an ARIMA model for the regression's errors.
Regressor chains - A regressor chain is a method for predicting several numerical outputs by arranging individual regression models in an ordered sequence.
Regret - Regret is the difference between a decision-maker's loss and the loss of a specified comparison strategy.
Regular expression - A regular expression is a pattern notation used to describe and match sets of strings.
Regularization - Regularization is any deliberate penalty added to training that discourages an overly complicated model, trading a slightly worse fit on past data for a...
Regularization function - A regularization function is the specific mathematical penalty term added to a training objective that quantifies how complex a model is, turning keep it...
Regularization path - A regularization path is the sequence of fitted model solutions obtained as the strength of a regularization penalty varies.
Regularization rate - The regularization rate is the dial that sets how strongly complexity is penalized during training: higher values force simpler models, lower values let the...
Regularized discriminant analysis - Regularized discriminant analysis is a classification approach that stabilizes estimated class covariance matrices through shrinkage.
Regularized empirical risk minimization - Regularized empirical risk minimization, or RERM, is a model-training principle that balances average loss on training data with a penalty expressing a...