Clipping - Clipping limits values to a chosen range, replacing anything above a maximum or below a minimum with the boundary value, and is used in AI to keep numbers...
Clitic - A clitic is a linguistic element that depends on a neighboring host for its pronunciation while contributing grammatical information.
Close-ended question - A close-ended question is a question that asks respondents to choose from a defined set of answers rather than compose an unrestricted response.
Closed class - A closed class is a grammatical word category whose membership is relatively stable and does not readily expand through ordinary creation of new words.
Closed-form matting - Closed-form matting is an image-matting method that estimates foreground opacity by constructing and solving a quadratic optimization problem under local...
Closed-loop - Closed-loop describes a system in which information about the system's behavior feeds back into decisions that influence its subsequent behavior.
Closed-world assumption - The closed-world assumption is a reasoning convention that treats relevant facts not established by the knowledge base as false.
Closeness - Closeness, or closeness centrality, measures how near a node is to other nodes in a graph according to shortest-path distances.
Closure, stop - A stop closure is the interval during production of a stop consonant when the relevant articulators form a complete obstruction in the vocal tract.
Cloud analytics - Cloud analytics is the use of cloud-based computing and data services to examine data and produce insights, reports or analytical models.
Cloud-based integration - Cloud-based integration connects applications, data and processes using capabilities hosted in a cloud environment.
Cloud computing - Cloud computing provides computing resources as network-accessible services that users can obtain and release on demand.
Cloud computing architecture - Cloud computing architecture is the arrangement of components, responsibilities and connections that delivers a cloud-based system.
Cloud computing security - Cloud computing security is the protection of cloud-hosted systems, data and services against unauthorized access, misuse, disruption and unintended exposure.
Cloud database - A cloud database is a database deployed using cloud computing resources.
Cloud-native computing - Cloud-native computing is an approach to building and operating systems that takes advantage of automated, dynamic computing environments.
Cloud resource elasticity - Cloud resource elasticity is the ability to expand and release computing resources as demand changes.
Cloud robotics - Cloud robotics uses network-accessible computation, data, or services to support robots and automation systems.
Cloud testing - Cloud testing is the use of cloud resources to support software testing, or the testing of systems deployed in cloud environments.
Cloudlet - A cloudlet is a small-scale computing environment placed near mobile devices or other data sources so it can provide nearby processing and storage.
Cloze task - A cloze task asks a person or model to supply missing material in a text using the available context.
Cluster assumption - The cluster assumption is a semi-supervised learning assumption that examples within the same meaningful high-density cluster tend to share a class.
Cluster centroid - A cluster centroid is a representative center used to summarize a cluster of data points.
Cluster hypothesis - The cluster hypothesis in information retrieval is the idea that documents that are closely associated tend to be relevant to the same information needs.
Cluster labeling - Cluster labeling is the process of assigning a human-readable description to a group of similar items.
Cluster-randomized controlled trial - A cluster-randomized controlled trial assigns groups, rather than individual people, at random to intervention or comparison conditions.
Cluster Sampling - Cluster sampling is a probability-sampling approach that selects groups of population units, such as branches, schools, or geographic areas.
Cluster-weighted modeling - Cluster-weighted modeling is a probabilistic approach that represents the joint distribution of inputs and outputs as a mixture of local models.
Clustered federated learning - Clustered federated learning is an approach to collaborative machine learning that groups clients with compatible learning needs and trains models for those...
Clustered file system - A clustered file system allows multiple computers in a coordinated cluster to access a shared file-system namespace while managing concurrent access and...
Clusterer - A clusterer is a model or algorithm that groups items by similarity, so that items in the same group are more alike each other than items in other groups...
Clustering - Clustering is the task of grouping items by similarity so that items within a group are more alike than items in different groups, discovered from the data...
Clustering assumption - The clustering assumption is the idea, used in semi-supervised learning, that data points falling in the same natural cluster probably share the same label...
Clustering error - Clustering error is a measure of how wrong a clustering's group assignments are, usually counted as the smallest number of items that would need to move...
Clustering high-dimensional data - Clustering high-dimensional data means grouping records described by many features, often hundreds or thousands.
Clustering illusion - The clustering illusion is the tendency to see meaningful patterns or causes in clusters and streaks that can arise through chance.
Clutter - Clutter, in tracking and data association, means detections that do not come from the target or targets of interest and instead create nuisance observations.
CN2 algorithm - The CN2 algorithm is a rule-induction method that learns classification rules from labeled examples.
Co-adaptation - Co-adaptation is a failure mode in neural networks where individual units become useful only in the company of specific other units, making the network...
Co-domain - The co-domain of a function is the declared set in which its output values lie. If a function is written f:U→V, U is its domain and V is its co-domain.
co-NP - co-NP, usually written coNP, is the class of decision problems whose complementary problems belong to NP.
co-NP-complete - A decision problem is co-NP-complete, or coNP-complete, when it belongs to coNP and every problem in coNP can be transformed into it by a polynomial-time...
Co-occurrence matrix - A co-occurrence matrix counts how often pairs of values appear together under a specified relationship.
Co-occurrence network - A co-occurrence network represents items as nodes and connects items that appear together within a defined context.
Co-training - Co-training is a semi-supervised method where two models learn the same task from two different views of the data, each labeling examples it is confident...
Coalescence Rule - The coalescence rule is a database dependency inference rule that combines a multivalued dependency with a suitably related functional dependency to...
Coarse-to-fine - Coarse-to-fine is a strategy that begins with a simplified or lower-detail representation and progressively introduces more detail.
Coarse-to-fine alignment - Coarse-to-fine alignment is a method for matching images by estimating their displacement at a reduced resolution and then refining that estimate at...