Private cloud computing infrastructure - Private cloud computing infrastructure is the computing, storage, networking and management foundation of a cloud provisioned for the exclusive use of one...
Privileged protected attribute - A privileged protected attribute refers, in common fairness-toolkit terminology, to a value or set of values of a protected attribute designated as the...
Pro-drop languages - Pro-drop languages allow certain pronouns to remain unspoken in grammatical constructions where their interpretation is supplied through grammar, context...
Proactive learning - Proactive learning is an extension of active learning that chooses both which example to label and which information source to ask.
Proaftn - PROAFTN is a fuzzy multicriteria classification method that assigns objects to predefined categories by comparing their characteristics with class...
Probabilistic automaton - A probabilistic automaton is a state-based computational model in which transitions can occur according to specified probabilities.
Probabilistic circuit - A probabilistic circuit represents a probability distribution through a computational graph of simple functions, weighted sums, and products.
Probabilistic classification - Probabilistic classification predicts probabilities for the possible classes of an observation rather than returning only a class label.
Probabilistic context-free grammar - A probabilistic context-free grammar, or PCFG, is a context-free grammar whose production rules have probabilities.
Probabilistic database - A probabilistic database represents uncertainty about database contents using a probability model.
Probabilistic forecasting - Probabilistic forecasting describes a future outcome using a probability distribution or useful parts of that distribution, such as quantiles and prediction...
Probabilistic Graphical Model - A probabilistic graphical model represents a probability distribution using a graph and associated numerical functions.
Probabilistic Horn abduction - Probabilistic Horn abduction is a framework that combines logical rules with probabilities assigned to possible hypotheses.
Probabilistic inference - Probabilistic inference is the process of using a probability model to calculate or approximate answers about uncertain quantities.
Probabilistic language model - A probabilistic language model assigns probabilities to sequences of language units, usually words or tokens, or to the next unit given its context.
Probabilistic logic programming - Probabilistic logic programming combines logical rules with explicit representations of uncertainty.
Probabilistic model - A probabilistic model represents uncertain quantities with random variables and probability distributions.
Probabilistic numerics - Probabilistic numerics treats numerical computation as inference about an unknown mathematical quantity.
Probabilistic principal component analysis - Probabilistic principal component analysis, or PPCA, is a probabilistic version of PCA that models an observed vector as a linear transformation of a...
Probabilistic Programming - Probabilistic programming is an approach to expressing statistical models as programs that represent uncertainty through probability distributions.
Probabilistic regression model - A probabilistic regression model predicts a numerical outcome together with a representation of uncertainty.
Probabilistic relaxation labeling - Probabilistic relaxation labeling is an iterative method for refining uncertain labels using compatibility relationships among neighboring items.
Probabilistic relevance model - A probabilistic relevance model is an information-retrieval model that ranks documents using estimates related to their probability of being relevant to a...
Probabilistic roadmap - A probabilistic roadmap is a graph built from sampled robot configurations and feasible local paths between them.
Probabilistic Sampling - Probabilistic sampling, usually called probability sampling, selects units through a random mechanism with known, positive inclusion probabilities for the...
Probabilistic semantics - Probabilistic semantics gives a precise probability-based meaning to statements in a knowledge representation system.
Probabilistic soft logic - Probabilistic soft logic, or PSL, is a framework for specifying probabilistic relational models using weighted logical rules.
Probabilistic Topic Model - A probabilistic topic model is a statistical model that represents a collection of documents through latent themes and probability distributions.
Probability - Probability is a numerical measure assigned to an event within a defined model of uncertainty.
Probability based disclosures - Probability based disclosures occur when released information enables a sensitive statement to be inferred with high probability even though the statement...
Probability box - A probability box, usually called a p-box, represents uncertainty about a probability distribution using lower and upper bounds on its cumulative...
Probability calibration - Probability calibration concerns whether predicted probabilities agree with observed event frequencies in an appropriate population.
Probability density function - A probability density function, often abbreviated PDF, describes how probability is distributed across the values of an absolutely continuous random variable.
Probability distribution - A probability distribution specifies how probability is assigned to the possible values of a random variable.
Probability integral transform - The probability integral transform maps a random variable through its own cumulative distribution function.
Probability management - Probability management is an approach to representing, communicating, and combining uncertainty as reusable data rather than reducing every uncertain input...
Probability mass function (pmf) - A probability mass function, or pmf, assigns a probability to each possible value of a discrete random variable.
Probability matching - Probability matching is a choice pattern in which alternatives are selected in proportions resembling their perceived probabilities or observed frequencies.
Probability model - A probability model is a mathematical description of uncertain outcomes and the probabilities assigned to them.
Probability of direction - Probability of direction, usually abbreviated pd, summarizes which side of a specified reference value has more posterior probability.
Probability of error - Probability of error is the probability that a specified decision or prediction is incorrect under a stated probability model or population distribution.
Probability of improvement - Probability of improvement is an acquisition criterion used in Bayesian optimization.
Probability plot - A probability plot compares ordered observations with corresponding theoretical quantiles from a proposed probability distribution.
Probability proportional to size - Probability proportional to size, often abbreviated PPS, describes sampling designs in which selection probabilities are linked proportionally to a known...