One-hot encoding - One-hot encoding turns a category into a set of yes-no columns: 'city' becomes one column per city, with a 1 in the item's own city and 0 everywhere else...
One-hot vector - A one-hot vector is the row of switches that represents one item's category: all zeros except a single 1 in the position of the category the item belongs to.
One right answer - One right answer, often abbreviated ORA in generative-AI evaluation discussions, describes a prompt with a single correct answer under its stated assumptions.
One-shot learning - One-shot learning is learning to recognize a category from a single example: show the system one photo of a new product, one recording of a new voice, and...
One-shot prompting - One-shot prompting gives a language model one demonstration of the desired task before asking it to handle a new input.
One-sided test - A one-sided test is a hypothesis test designed to detect a departure in one specified direction.
One-standard-error rule - The one-standard-error rule selects a simpler model whose estimated validation error is no more than one estimated standard error above the smallest...
One-to-many (data model) - A one-to-many relationship connects one instance of an entity type to potentially several instances of another, while each instance on the many side relates...
One-to-one (data model) - A one-to-one relationship is a data-model relationship in which each instance on either side is associated with at most one instance on the other side.
One-vs-one - One-vs-one is a scheme for multi-class classification that trains one binary classifier for every pair of classes: ten classes mean forty-five pairwise...
One-vs-Rest - One-vs-Rest is a scheme for multi-class classification that trains one binary model per class, each answering a single question: is this item a member of my...
One-way analysis of variance - One-way analysis of variance is a statistical framework for comparing the means of groups defined by a single factor.
One-way ANOVA - One-way ANOVA is the abbreviated name for one-way analysis of variance: a method for comparing quantitative outcomes across groups defined by one factor.
Online algorithm - An online algorithm processes input as it arrives and makes required decisions without knowing the entire future input sequence.
Online complex processing - Online complex processing, or OLCP, is a historical database-workload term for demanding online operations that can combine complex queries, multi-statement...
Online expectation maximization - Online expectation maximization (online EM) updates a latent-variable model as observations arrive, rather than repeatedly processing the entire dataset in...
Online gradient descent - Online gradient descent is a method that updates a decision or model using the gradient of the loss revealed after each round.
Online inference - Online inference is the use of a trained model to generate a prediction when an application requests it.
Online Inference Pipeline - An online inference pipeline is the sequence of processing steps that turns a prediction request into a response using a deployed machine-learning model.
Online-Offline Feature Skew - Online-offline feature skew is the mismatch that appears when a feature is computed one way in the training data and a subtly different way in the live...
Online One-Class SVM - An online one-class SVM is a novelty detector trained mostly on examples of normal behavior and updated as new normal data arrives, flagging whatever does...
Online optimization - Online optimization studies how to make a sequence of decisions when relevant information arrives over time and future costs are not yet known.
Online replanning - Online replanning is the process of revising a plan while an agent is carrying out its task, using new observations or changed conditions.
Online search - Online search is problem solving that interleaves computation with actions and observations in an environment.
Online Store - An online store is the part of a feature-store architecture designed to retrieve feature values quickly for prediction requests, usually using one or more...
Ontological commitment - An ontological commitment is a choice about what kinds of things a representation treats as existing and how its vocabulary refers to them.
Ontological engineering - Ontological engineering is the disciplined work of designing, evaluating, and maintaining explicit models of the concepts and relationships in a domain.
Ontology - An ontology is an explicit model of the concepts, entities, and relationships relevant to a domain, with definitions that clarify their meanings.
Ontology alignment - Ontology alignment identifies and represents meaningful correspondences between entities in different ontologies.
Ontology-based data integration - Ontology-based data integration uses an ontology as an explicit model of meaning to connect information from different sources.
Ontology engineering - Ontology engineering is the systematic development and maintenance of a shared model of domain concepts, relationships, and assumptions.
Ontology learning - Ontology learning is the automatic or partly automatic development of a structured domain model from data.
Ontology merging - Ontology merging is the construction of a combined ontology from two or more source ontologies.
Opacity - Opacity is difficulty seeing or understanding how an AI system operates, reaches an output or affects a decision.
Open access - Open access is the online availability of scholarly work without a reader payment barrier, with reuse permissions an important part of fuller definitions.
Open class - Definition: An open class is a grammatical category that readily admits new words.
Open coding - Open coding is an exploratory qualitative-analysis process in which a researcher examines data closely and develops initial labels for concepts, actions or...
Open data index - An open data index is a structured assessment of how openly selected datasets are published.
Open-ended question - An open-ended question invites a respondent to provide an answer in their own words rather than choose only from a predetermined set of response options.
Open information extraction - Open information extraction is a natural-language processing task that extracts relationships from text without requiring a fixed list of relation types in...
Open-label trial - An open-label trial is an intervention study in which participants and the investigators providing the intervention know which treatment or strategy each...
Open-loop - Open-loop describes a control or action process that does not use feedback from the controlled result to revise its commands during the relevant execution...
Open set recognition - Open set recognition is a recognition setting in which a system must identify supported classes while allowing inputs from previously unseen classes to be...
Open-source artificial intelligence - Open-source artificial intelligence refers to AI systems released with permissions and materials that enable others to use, inspect, modify and share them.
Open-source robotics - Open-source robotics develops or uses robot software, hardware designs, or both under licenses that permit access, modification, and redistribution under...
Open-universe probability model - An open-universe probability model represents uncertainty about which objects exist, how many there are, and how observations refer to them.