Bessel's correction - Bessel's correction replaces division by n with division by n − 1 when estimating a population variance from n observations using their sample mean.
Best bin first - Best Bin First, or BBF, is an approximate nearest-neighbor search method that explores promising regions of a k-d tree in priority order.
Best-first search - Best-first search is a family of search methods that repeatedly expands the most promising waiting node according to an evaluation function.
Best node search - Best Node Search, or BNS, is a game-tree search method that aims to identify the best move without necessarily calculating its exact minimax value.
Best-worst scaling - Best-worst scaling is a comparative annotation method in which a person selects the highest and lowest items on a specified property from a small group.
Beta-binomial model - A beta-binomial model combines a binomial model for a count of successes with a beta distribution for the underlying success probability.
Between-group design experiment - A between-group design experiment compares outcomes from separate groups exposed to different experimental conditions.
Betweensubjects designs - Between-subjects designs are study arrangements in which different participants experience the different levels of a factor.
Bhattacharyya distance - Bhattacharyya distance measures dissimilarity between probability distributions by taking the negative logarithm of their Bhattacharyya coefficient, a...
Bi-tempered loss - Bi-tempered loss is a generalization of logistic classification loss that uses two temperature parameters: one changes how prediction errors are penalized...
Bias - Bias is a systematic tendency, distortion or preference whose meaning depends on context.
Bias detection and mitigation - Bias detection and mitigation is the process of identifying relevant systematic distortions or unfair patterns in an AI workflow, investigating their causes...
Bias (math) or bias term - A bias term is an adjustable constant added to a model's weighted input.
Bias mitigation algorithm - A bias mitigation algorithm is a computational procedure intended to reduce a specified unwanted bias or fairness disparity in data, model training or outputs.
Bias testing - Bias testing is a structured examination of data, models or AI-enabled decisions for specified systematic distortions or unfair patterns.
Bias-variance trade-off - The bias - variance trade-off describes how a learning method's systematic prediction error and sensitivity to its training sample can interact.
Biased estimator - A biased estimator is a rule for estimating a population quantity whose expected result differs from that quantity under the specified sampling model.
Biclustering - Biclustering is a way of finding related subsets of rows and columns together in a data matrix.
Biconditional - A biconditional is a logical statement meaning if and only if.
Biconnected components - Biconnected components are maximal connected parts of an undirected graph that have no internal articulation point: removing a single vertex does not split...
Bicubic - Bicubic interpolation estimates image values between sampled locations using cubic functions in two dimensions.
Bidiagonal matrix - A bidiagonal matrix is a matrix whose only potentially nonzero entries lie on the main diagonal and one immediately neighboring diagonal.
Bidirectional - In AI, bidirectional describes a model that reads a sequence in both directions at once, from start to end and from end to start, so each word or item is...
Bidirectional associative memory - Bidirectional associative memory, or BAM, is a neural associative-memory model that stores relationships between pairs of patterns and can use a cue on...
Bidirectional language model - A bidirectional language model uses context before and after a target position to model language at that position.
Bidirectional search - Bidirectional search looks for a connection by searching forwards from a starting state and backwards from a goal.
Bidirectional similarity - Bidirectional similarity is an image-comparison objective that checks patch matches in both directions between a source and a result.
Bidirectional Transformer Language Model - A Bidirectional Transformer Language Model uses Transformer layers that allow a token's representation to incorporate surrounding context from both earlier...
Big data ethics - Big data ethics examines the responsibilities and consequences involved in collecting, linking, analyzing, sharing and acting on large or complex datasets.
Big data maturity model - A big data maturity model is a framework for assessing how effectively an organization can manage and use large or complex datasets.
Big M method - The Big M method is a linear-programming technique that adds artificial variables to obtain a convenient starting basis and assigns them a very large...
Bigram - A bigram is a pair of neighboring items in a sequence, usually two adjacent words such as New York or not good, counted or predicted together so a little...
Bilabial - Bilabial describes a speech sound whose primary constriction is made using both lips.
Bilateral filtering - Bilateral filtering is an edge-preserving smoothing method that weights neighboring pixels by both spatial closeness and similarity in value.
Bilateral grid - A bilateral grid is a data structure that organizes image information by both pixel location and a guiding value, such as brightness.
Bilevel optimization - Bilevel optimization is optimization in which one decision problem contains another decision problem as a constraint.
Bilinear interpolation - Bilinear interpolation estimates a value between four neighboring samples on a rectangular grid by interpolating in two directions.
Bilinear transform - The bilinear transform is a mathematical substitution used to convert a continuous-time filter description into a discrete-time filter.
Bimodal - Bimodal describes a distribution with two distinct peaks, or modes. Values tend to concentrate around two regions rather than one.
Binary branching - Binary branching describes a tree structure in which a branching node has two immediate children.
Binary classification - Binary classification is the task of sorting items into exactly two categories, such as spam or not spam, churn or stay, approve or decline.
Binary condition - A binary condition is a yes-or-no test, such as order value above 100 or country is France, used at each node of a decision tree or rule set to send every...
Binary constraint - A binary constraint is a restriction involving exactly two variables in a constraint satisfaction problem. It specifies which pairs of values are allowed.
Binary cross-entropy - Binary cross-entropy, often abbreviated BCE, is a loss function for assessing predicted probabilities of a binary outcome.
Binary decision - A binary decision is a choice between two defined alternatives, such as yes or no, accept or reject, or object present or absent.
Binary Decomposition - Binary decomposition divides one relation schema into two relation schemas whose attributes collectively cover the original schema.
Binary image - A binary image is an image whose pixels have only two possible values.