Entropy coding - Entropy coding is lossless coding that uses the relative likelihood of symbols or symbol sequences to represent data compactly.
Entropy estimation - Entropy estimation is the statistical task of estimating a probability distribution's entropy from observed data.
Entropy minimization in semisupervised learning - Entropy minimization in semisupervised learning is a training approach that encourages a classifier to make concentrated, low-entropy class predictions on...
Entropy power inequality - The entropy power inequality is an information-theoretic result bounding the entropy power of a sum of independent continuous random variables or vectors.
Entropy rate - Entropy rate is the limiting average uncertainty per observation in a stochastic process.
Entry-sequenced organization - Entry-sequenced organization is a way of arranging stored records according to the order in which they enter a data set.
Entry SQL - Entry SQL is the entry-level conformance category associated with the historical SQL-92 standard.
Entry time - Entry time is the point at which a person or other unit begins contributing observations or risk time to a study.
Enumeration Domain - An enumeration domain is a domain whose permitted values are explicitly listed, such as draft, submitted, and approved for a document status.
Enumeration Encoding - Enumeration encoding assigns a distinct code to each value in a defined set of alternatives.
Enumeration Table - An enumeration table is a table that lists the allowed alternatives for a category, usually with a stable code and a readable label.
Environment - In AI, an environment is the world an agent acts in: everything outside the agent that it can observe, influence and receive consequences from.
Environment class - An environment class is a collection of possible environments used to specify, study, or evaluate an intelligent agent.
Environment grounding - Environment grounding is anchoring an agent's outputs in the actual state of its environment, through fresh observations, tool results or retrieved data...
Epanechnikov kernel - The Epanechnikov kernel is a compactly supported, parabolic weighting function used in statistical smoothing, especially kernel density estimation.
Epigraph - The epigraph of a function is the set of points on or above its graph.
Epipolar geometry - Epipolar geometry describes the geometric relationship between two views of a three-dimensional scene taken from different camera positions.
Episode - An episode is one complete run of an agent's task, from its starting situation to a natural end, such as one game, one delivery or one customer conversation.
Episodic memory - Episodic memory is an agent's store of specific past experiences it can look back at: particular events, conversations or attempts, rather than generalized...
Epistemic modal logic - Epistemic modal logic is a formal system for reasoning about knowledge, including what one agent knows about the world and about other agents' knowledge.
Epoch - An epoch is one complete pass through the entire training dataset during a model's training; training usually runs for many epochs.
Epsilon-ball - An epsilon-ball is a neighborhood of points within a specified distance epsilon of a chosen center.
Epsilon greedy policy - An epsilon greedy policy is a decision rule that usually chooses an action with the highest current estimated value but sometimes explores through random...
Equal impact - Equal impact is a fairness objective concerned with the benefits and costs that a decision system creates for affected people.
Equality of opportunity - In binary machine-learning fairness, equality of opportunity usually means that the true-positive rate is the same across the groups being compared.
Equality symbol - The equality symbol, usually written =, states in first-order logic that two terms refer to the same object.
Equalized odds - Equalized odds is a statistical fairness criterion requiring a model's predictions to be independent of group membership once the actual target outcome is...
Equally weighted means - Equally weighted means are averages formed by giving each component mean the same weight, regardless of how many observations contributed to it.
Equational unification - Equational unification finds substitutions for variables that make two symbolic expressions equal according to a specified collection of equations.
Equi-join - An equi-join combines rows from two relations or tables using equality comparisons between specified values.
Equivalence test - An equivalence test assesses whether an effect lies within prespecified bounds representing differences small enough to be considered practically...
Error cost function - An error cost function assigns a loss or cost to a forecasting error.
Error-driven learning - Error-driven learning adjusts a model using a discrepancy between its output and a desired or observed outcome.
Error exponent - An error exponent describes how quickly an error probability decreases on an exponential scale as the amount of information or the block length grows.
Error level analysis - Error level analysis, or ELA, is an image-inspection technique that visualizes differences between a lossy-compressed image and a recompressed version of it.
Error propagation - Error propagation is the way an error or uncertainty in one part of a process affects later calculations, predictions, or decisions.
Error rate - Error rate is the proportion of evaluated units counted as incorrect under a defined rule.
Error rate per comparison ( PC ) - Error rate per comparison is the probability of falsely rejecting the null hypothesis for a particular comparison when that null is true.
Error (Statistical error) - Statistical error is the difference between a value obtained through data collection or estimation and the corresponding true population value or other...
Error variance - Error variance is the variance of the error term in a specified statistical model.
Errors of prediction - Errors of prediction are the differences between observed outcomes and their corresponding predicted values.
Essential matrix - The essential matrix is a three-by-three matrix that represents the epipolar relationship between two calibrated camera views.
Estimand - An estimand is the precise quantity that a study aims to learn about.
Estimate - An estimate is a value calculated from observed data to represent an unknown quantity, such as a population mean, proportion, total, or model parameter.
Estimation - Estimation is the process of using observed data to infer unknown quantities, such as population characteristics or model parameters.
Estimation error - Estimation error is the discrepancy between an estimated quantity and its true or explicitly defined target.