E-optimal design - E-optimal design chooses an experimental allocation that maximizes the smallest eigenvalue of its information matrix.
E-values - E-values are nonnegative statistical evidence values obtained from random variables whose expected value is at most one under every distribution allowed by...
Eager learning - Eager learning builds a general predictive model from training examples before new prediction requests arrive.
Early-arriving fact - An early-arriving fact is a measured business event that reaches a data warehouse before its full descriptive context is available.
Early exit - Early exit is a deep-learning inference strategy that produces a prediction before an input has passed through every layer of a network.
Early goal test - An early goal test checks whether a newly generated search node satisfies the goal before the node is later selected from the frontier for expansion.
Early stopping - Early stopping is ending a model's training at the point where it performs best on fresh data, before it starts memorizing the training set.
Earth mover's distance - Earth mover's distance, or EMD, measures how much work is needed to transform one distribution of mass into another when moving mass has a specified cost.
Echo State Network - An echo state network, or ESN, is a recurrent neural-network approach in which a dynamic reservoir transforms input sequences into internal states and a...
Ecological Fallacy Bias - The ecological fallacy is the mistake of treating a relationship or characteristic observed for groups as if it necessarily held for individuals within...
Ecological study - An ecological study investigates relationships using groups, populations, places, or time periods as the units of analysis.
Edge-augmentation - Edge-augmentation is the process of adding edges to a graph to achieve a desired structural property.
Edge case - An edge case is an input or situation near the limits of a system's assumptions, rules, or operating conditions, or an unusual combination that challenges...
Edge computing - Edge computing places some data processing close to the devices, people or physical processes that produce or use the data.
Edge data integration - Edge data integration, in the business-user sense used here, connects data to meet a particular local need alongside centrally provided enterprise...
Edge detection - Edge detection identifies locations in an image where intensity, color, or another image quantity changes in a way associated with a boundary.
Edge device - An edge device is a computing device operating at or near the part of a network where data is produced or first processed.
Edge-directed interpolation - Edge-directed interpolation estimates missing image samples by adapting to local edge structure.
Edge enhancement - Edge enhancement changes an image to make transitions near edges more pronounced.
Edge-factored - Edge-factored describes a structured model whose score for a graph or tree decomposes into contributions from its individual edges.
Edge-preserving filter - An edge-preserving filter processes an image while trying to avoid blurring important transitions between regions.
Edge-preserving smoothing - Edge-preserving smoothing reduces selected image variations while trying to retain meaningful boundaries between regions.
Edge-spread function - An edge-spread function, or ESF, describes how an imaging system represents a sharp step boundary as a profile of image values across that boundary.
Edge weight - An edge weight is a numerical value associated with a connection between two nodes in a graph.
Edgelist - An edgelist, or edge list, represents a graph by listing its connections, usually one edge per record with two endpoint identifiers and optional edge...
Edit distance - Edit distance measures the minimum cost of changing one sequence into another using a specified set of edit operations.
Edmonds-Karp - Edmonds-Karp is an algorithm for finding a maximum flow from a source to a sink in a capacitated network.
EDU - EDU stands for elementary discourse unit: a minimal segment used as a building block in a discourse analysis, especially Rhetorical Structure Theory.
Effect size - Effect size is a numerical description of how large a difference or association is.
Effective branching factor - The effective branching factor is a summary measure that compares a search's node count with a hypothetical uniform tree of the same solution depth.
Effective degrees of freedom - Effective degrees of freedom quantify the flexibility or statistical complexity used by a fitting procedure, under a specified definition.
Effective depth - Effective depth is an analytical way to describe search effort as though a search had explored a shallower tree than an uninformed baseline.
Effective dimension - Effective dimension is a measure of how many independent directions or degrees of freedom substantially contribute to a model or learning problem.
Effective model dimensionality - Effective model dimensionality describes how many independent directions of model flexibility are meaningfully determined or used under a specified dataset...
Effective sample size - Effective sample size is the size of a specified reference sample that would provide comparable statistical information or precision for a particular analysis.
Efficiently updatable neural network - An efficiently updatable neural network, commonly called NNUE, is an architecture designed to reuse computations when successive inputs change only slightly.
Efros - Leung texture synthesis - Efros - Leung texture synthesis is an example-based method that grows a new texture image one pixel at a time using a supplied texture sample.
Egocentric vision - Egocentric vision studies visual information captured from the perspective of the person or agent performing an activity.
Eigenmoments - Eigenmoments are image descriptors obtained by applying eigenanalysis to a space of geometric image moments.
Eigenvalue - An eigenvalue is a number that describes how a square matrix scales a corresponding nonzero eigenvector.
Eigenvector - An eigenvector is a nonzero vector that a square matrix transforms into a scalar multiple of itself.
Einsum notation - Einsum notation is a compact way of writing operations on multi-dimensional arrays by naming their axes, so sums, products, transposes and contractions are...
Elastic map - An elastic map is a method for approximating a dataset with a low-dimensional structure embedded in the original data space.
Elastic-Net - Elastic-Net is a regression method that combines the two classic penalty types, L1 and L2, so it selects variables like the first and stabilizes estimates...
Electronic image stabilization - Electronic image stabilization reduces unwanted apparent camera motion by digitally adjusting captured images or video frames.
Electronic seal - An electronic seal is electronic data associated with other electronic information to support verification of its origin and integrity.
Elementary Domain - Elementary domain is a database-modeling term for a basic value domain, such as numbers, character strings, or dates, used as a building block for attributes.