SettingsProbabilistic models
Bayesian brain
Bayesian brain is a term that is used to refer to the ability of the nervous system to operate in situations of uncertainty in a fashion that is close to the optimal prescribed by Bayesian stati...
Bayesian brain is a term that is used to refer to the ability of the nervous system to operate in situations of uncertainty in a fashion that is close to the optimal prescribed by Bayesian stati...
Binary Independence Model
The Binary Independence Model (BIM) is a probabilistic information retrieval technique that makes some simple assumptions to make the estimation of document/query similarity probability feasible.
The Binary Independence Model (BIM) is a probabilistic information retrieval technique that makes some simple assumptions to make the estimation of document/query similarity probability feasible.
Constellation model
The constellation model is a probabilistic, generative model for category-level object recognition in computer vision.
The constellation model is a probabilistic, generative model for category-level object recognition in computer vision.
Divergence-from-randomness model
In the field of information retrieval, divergence from randomness is one type of probabilistic model.
In the field of information retrieval, divergence from randomness is one type of probabilistic model.
Factored language model
The factored language model (FLM) is an extension of a conventional language model.
The factored language model (FLM) is an extension of a conventional language model.
First-order reliability method
The first-order reliability method,, is a semi-probabilistic reliability analysis method devised to evaluate the reliability of a system.
The first-order reliability method,, is a semi-probabilistic reliability analysis method devised to evaluate the reliability of a system.
Generative model
In probability and statistics, a generative model is a model for randomly generating observable data, typically given some hidden parameters.
In probability and statistics, a generative model is a model for randomly generating observable data, typically given some hidden parameters.
Maier's theorem
In number theory, Maier's theorem is a theorem about the numbers of primes in short intervals for which the Cramér's probabilistic model of primes give the wrong answer.
In number theory, Maier's theorem is a theorem about the numbers of primes in short intervals for which the Cramér's probabilistic model of primes give the wrong answer.
Mixture model
In statistics, a mixture model is a probabilistic model for representing the presence of sub-populations within an overall population, without requiring that an observed data-set should identify...
In statistics, a mixture model is a probabilistic model for representing the presence of sub-populations within an overall population, without requiring that an observed data-set should identify...
N-gram
In the fields of computational linguistics and probability, an n-gram is a contiguous sequence of n items from a given sequence of text or speech.
In the fields of computational linguistics and probability, an n-gram is a contiguous sequence of n items from a given sequence of text or speech.
Probabilistic automaton
In mathematics and computer science, the probabilistic automaton (PA) is a generalization of the non-deterministic finite automaton; it includes the probability of a given transition into the tr...
In mathematics and computer science, the probabilistic automaton (PA) is a generalization of the non-deterministic finite automaton; it includes the probability of a given transition into the tr...
Probabilistic relational model
A Probabilistic relational model (PRM) is the counterpart of a Bayesian network in statistical relational learning.
A Probabilistic relational model (PRM) is the counterpart of a Bayesian network in statistical relational learning.
Probabilistic relational programming language
A probabilistic relational programming language(PRPL) is a programming language specially designed to describe and infer with probabilistic relational model(PRM)s.
A probabilistic relational programming language(PRPL) is a programming language specially designed to describe and infer with probabilistic relational model(PRM)s.
Probabilistic relevance model
The probabilistic relevance model was devised by Robertson and Jones as a framework for probabilistic models to come.
The probabilistic relevance model was devised by Robertson and Jones as a framework for probabilistic models to come.
Probabilistic relevance model (BM25)
In information retrieval, Okapi BM25 is a ranking function used by search engines to rank matching documents according to their relevance to a given search query.
In information retrieval, Okapi BM25 is a ranking function used by search engines to rank matching documents according to their relevance to a given search query.
Probabilistic voting model
The probabilistic voting theory, also known as the probabilistic voting model, is a voting theory developed by professor Peter J. Coughlin, 1992, which has gradually replaced the median v...
The probabilistic voting theory, also known as the probabilistic voting model, is a voting theory developed by professor Peter J. Coughlin, 1992, which has gradually replaced the median v...
Stochastic context-free grammar
A stochastic context-free grammar (SCFG; also probabilistic context-free grammar, PCFG) is a context-free grammar in which each production is augmented with a probability.
A stochastic context-free grammar (SCFG; also probabilistic context-free grammar, PCFG) is a context-free grammar in which each production is augmented with a probability.