Split-half reliability - Split-half reliability is an approach to assessing measurement consistency by dividing a set of measurement contributions into two parts and comparing the...
Split point - A split point is a threshold used to divide examples according to the value of a numerical feature, especially in a decision tree.
Splitter - In decision-tree training, a splitter is the procedure that selects the condition used to divide examples at a node.
Spoken dialog system - A spoken dialog system is a computer system that interacts with a person through spoken conversation.
Spot instance - A spot instance is a cloud computing instance offered from spare capacity under terms that allow the provider to reclaim it.
Spreading activation - Spreading activation is a process in which activity assigned to one node in a network influences connected nodes.
Spreadmart - A spreadmart is a locally maintained reporting or analysis system, commonly built with spreadsheets or desktop databases, that performs functions associated...
Spurious Tuple - A spurious tuple is an extra tuple produced when relations are joined in a way that reconstructs combinations not present in the original relation being...
Squared error loss - Squared error loss measures the mismatch between a numerical prediction and its target by squaring their difference.
Squared hinge loss - Squared hinge loss is a classification loss that squares the positive shortfall from a target margin.
Squared ranks test - The squared ranks test, often called the Conover squared ranks test, is a rank-based procedure for comparing dispersion across independent groups.
SSS* - SSS* is a best-first game-tree search algorithm for computing a minimax value.
Stability - Stability describes how little an output changes under specified disturbances.
Stable model - A stable model is a formally defined interpretation of a logic program with default negation.
Stack search - Stack search is a search strategy that keeps a ranked collection of partial solutions, repeatedly expands a promising candidate, and inserts the resulting...
Stacked generalization - Stacked generalization, often called stacking, combines predictions from several models using another model that learns how to combine them.
Stacked RNNs - Stacked RNNs are recurrent neural networks arranged in multiple recurrent layers, with the output sequence from one layer feeding the next.
Staged training - Staged training trains a machine-learning model through a planned sequence of distinct phases.
Staged tree (mathematics) - A staged tree is a probabilistic event tree whose nonterminal situations are grouped into stages when they share the same conditional distribution over...
Staging (data) - Data staging is the use of an intermediate location to hold data between its source and a later processing or delivery step.
Staleness - Staleness is the degree to which information used by a distributed computation lags behind the relevant current state.
Stance detection - Stance detection is the task of identifying the position expressed or implied by text towards a specified target, such as a proposal, product or claim.
Standard deviation - Standard deviation is a measure of spread obtained by taking the square root of variance.
Standard error - The standard error is the standard deviation of an estimator's sampling distribution.
Standard error of differences between means - The standard error of differences between means is the standard deviation of the sampling distribution of a difference between estimated means.
Standard lottery - A standard lottery is a reference gamble used in expected-utility assessment, typically offering a defined best outcome with probability p and a defined...
Standard normal distribution - The standard normal distribution is the normal, or Gaussian, probability distribution with mean zero and variance one.
Standard normal random vector - A standard normal random vector is a vector whose components are independent standard normal random variables.
Standard scores - Standard scores express observations on a reference scale with a specified mean and standard deviation.
Standard test image - A standard test image is a commonly used reference image for examining or comparing image-processing methods.
Standardization - Standardization, in the statistical preprocessing sense used here, transforms a variable by subtracting a chosen mean and dividing by a chosen positive...
Standardized coefficient - A standardized coefficient is a regression coefficient expressed using standardized variable scales.
Standardizing apart - Standardizing apart is the logical operation of consistently renaming variables so that variables belonging to separate clauses, scopes or rule applications...
Start symbol - A start symbol is the designated symbol from which a formal grammar begins deriving complete expressions.
State - In reinforcement learning and agent systems, a state describes the situation relevant to deciding what happens next.
State abstraction - State abstraction is the process of mapping detailed states of a problem into simpler states that retain selected information.
State machine agent - A state machine agent is an agent built as an explicit set of states and transitions: it is always in one known state, such as waiting, collecting details...
State observer - A state observer is a model-based system that estimates the internal state of a dynamic process from its measured outputs and known inputs.
State space - A state space is the set of possible states used to represent a system.
State space graph - A state space graph represents the possible states of a problem and the actions that connect them.
State-space landscape - A state-space landscape is a way to understand an optimization problem by treating candidate states as locations and their objective values as heights.
State space modeling - State space modeling describes a changing system using an underlying state and equations connecting that state to observations.
State-space search - State-space search is the process of exploring possible states and transitions to find a solution to a modeled problem.
State-value function - A state-value function assigns each state the expected future return obtained by starting there and following a specified policy.
Statement - In this robotics knowledge-base context, a Statement is a structured assertion represented as a subject, predicate, and object triple.
Static embeddings - Static embeddings are vector representations that assign the same representation to a word or other vocabulary unit regardless of its surrounding context at...
Static quality scores - Static quality scores are document-level ranking signals that do not depend on the current query.
Stationarity - Stationarity is a property describing statistical stability over time.