Local regression - Local regression estimates a response curve or surface by fitting simple regressions to neighborhoods of observations.
Local search - Local search is a family of methods that looks for useful solutions by modifying current candidate solutions and evaluating nearby alternatives.
Local tangent space alignment - Local tangent space alignment, or LTSA, is a nonlinear dimensionality-reduction method that estimates local tangent spaces around data points and aligns...
Local tone mapping - Local tone mapping adjusts an image's tonal values using information about each location's surroundings.
Locale (computer hardware) - A locale is an abstraction representing a group of computing and memory resources within a parallel system.
Localist representation - A localist representation assigns a particular concept or item to a dedicated representational unit.
Locality-sensitive hash - A locality-sensitive hash is a hash designed so that similar items are more likely than dissimilar items to receive the same value.
Localization - Localization is the process of estimating a robot's position and orientation relative to a reference frame or environment.
Locally adaptive regression kernel (LARK) - A locally adaptive regression kernel (LARK) is a description of a pixel's neighborhood whose shape adapts to local image structure.
Locally weighted learning - Locally weighted learning makes a prediction by emphasizing training examples relevant to the query being answered.
Locally weighted regression - Locally weighted regression predicts a response by fitting a regression that gives greater influence to observations near the query point.
Location-based recommendation - Location-based recommendation is the selection or ranking of suggested items using geographical context as part of the decision.
Location test - A location test is a statistical hypothesis test about where a distribution is centered.
Locative adverb - A locative adverb is an adverb that expresses where an action or situation occurs or, in a broad spatial use of the term, the direction associated with it.
Locking - In historical automated theorem proving, locking is a restriction on resolution that uses labels on literal occurrences to control which inferences are...
Locks with ordered sharing - Locks with ordered sharing are database concurrency-control mechanisms that permit selected conflicting operations to proceed in a required order while...
Loess - Loess is a local regression method that estimates a smooth relationship by fitting low-degree polynomials to nearby observations.
Log area ratio - A log area ratio, or LAR, is a transformed parameter used in speech-signal modeling and coding, commonly derived from a reflection coefficient.
Log encoding - Log encoding represents image signals with a logarithmic or partly logarithmic transfer function.
Log-Gaussian Cox process - A log-Gaussian Cox process is a model for randomly located events in which the logarithm of an underlying event intensity follows a Gaussian process.
Log likelihood - Log likelihood is the logarithm of a likelihood function, usually using the natural logarithm.
Log likelihood ratio - A log likelihood ratio compares how well two statistical models or hypotheses account for the same observed data by taking the logarithm of their likelihood...
Log-linear models - Log-linear models describe expected counts by making their logarithms linear combinations of parameters.
Log Loss - Log Loss, also called cross-entropy loss, is the standard error measure for probabilistic classifiers: it punishes wrong confident predictions severely...
Log-normal distribution - A log-normal distribution describes a positive random quantity whose logarithm follows a normal distribution.
Log-odds - Log-odds is the logarithm of the odds of an event: a way of stretching probability from its cramped zero-to-one scale onto an open number line where adding...
Log odds ratio - A log odds ratio is the logarithm of the ratio between two odds. It compares the relative odds of the same event in two groups or conditions.
Log probabilities - Log probabilities are logarithms of probabilities.
Log shipping - Log shipping maintains a secondary database by transferring and applying transaction-log information from a primary database.
Log-sum-exp trick - The log-sum-exp trick is a numerically stable way to calculate the logarithm of a sum of exponentials.
Log trigger - A log trigger is a database trigger used to record changes to a table in a separate log or history table.
Logarithm - A logarithm gives the exponent needed to raise a specified base to a positive number. If b raised to y equals x, then log base b of x equals y.
Logarithmic transformation - A logarithmic transformation replaces positive values with their logarithms.
Logic - Logic provides formal ways to express statements and determine what follows from them.
Logic form - A logic form, in the NLP convention covered here, is a structured representation of a sentence using predicates and shared arguments.
Logic learning machine - Logic Learning Machine is a rule-learning approach associated with Marco Muselli's switching neural network work and implemented in the Rulex software.
Logical connectives - Logical connectives are operators that combine or modify statements to form more complex statements.
Logical Data Model - A logical data model describes how information is organized into defined structures, attributes and relationships without specifying the detailed physical...
Logical equivalence - Logical equivalence means that two statements have the same truth value in every interpretation allowed by the chosen logic.
Logical Independence - Logical independence, in database architecture, is the ability to change the conceptual or logical schema without requiring corresponding changes to an...
Logical inference - Logical inference is the process of deriving conclusions from premises using specified reasoning rules.
Logical minimization - Logical minimization, in the circumscription sense used in knowledge representation, prefers models that make selected predicates true of as few cases as...
Logical omniscience - Logical omniscience is an idealization in which an agent is treated as knowing every logical consequence of what it knows, as well as every logical validity.
Logical schema - A logical schema describes how a domain's data is structured, including its entities or record types, attributes, relationships and relevant constraints...
Logico-linguistic modeling - Logico-linguistic modeling is an approach to knowledge elicitation and representation that extends soft systems modeling with explicit logical treatment of...
Logistic function - The logistic function maps a real-valued input to an S-shaped output.
Logistic loss - Logistic loss is a smooth loss function for binary prediction that penalizes confidence assigned to the wrong outcome.