See Bayesian network on Wiktionary
{ "etymology_text": "Named after Thomas Bayes (1701–1761), English mathematician.", "forms": [ { "form": "Bayesian networks", "tags": [ "plural" ] } ], "head_templates": [ { "args": {}, "expansion": "Bayesian network (plural Bayesian networks)", "name": "en-noun" } ], "lang": "English", "lang_code": "en", "pos": "noun", "senses": [ { "categories": [ { "kind": "other", "name": "English entries with incorrect language header", "parents": [ "Entries with incorrect language header", "Entry maintenance" ], "source": "w" }, { "kind": "other", "name": "Pages with 1 entry", "parents": [], "source": "w" }, { "kind": "other", "name": "Pages with entries", "parents": [], "source": "w" }, { "kind": "topical", "langcode": "en", "name": "Statistics", "orig": "en:Statistics", "parents": [ "Formal sciences", "Mathematics", "Sciences", "All topics", "Fundamental" ], "source": "w" } ], "glosses": [ "A directed acyclic graph whose vertices represent random variables and whose directed edges represent conditional dependencies. Each random variable can fall into any of at least two mutually disjoint states, and has a probability function which takes as inputs the states of its parent nodes and returns as output the probability of being in a certain state for a given combination of the states of its parent nodes. A node without parent nodes just has an unconditioned probability of being in some given state." ], "hypernyms": [ { "word": "graphical model" }, { "word": "probabilistic graphical model" } ], "id": "en-Bayesian_network-en-noun-Pd0x1GPo", "links": [ [ "statistics", "statistics" ], [ "random variable", "random variable" ], [ "conditional", "conditional probability" ] ], "raw_glosses": [ "(statistics) A directed acyclic graph whose vertices represent random variables and whose directed edges represent conditional dependencies. Each random variable can fall into any of at least two mutually disjoint states, and has a probability function which takes as inputs the states of its parent nodes and returns as output the probability of being in a certain state for a given combination of the states of its parent nodes. A node without parent nodes just has an unconditioned probability of being in some given state." ], "topics": [ "mathematics", "sciences", "statistics" ], "wikipedia": [ "Bayesian network", "Thomas Bayes" ] } ], "sounds": [ { "ipa": "/ˈbeɪ.zjən ˈnɛt.wɜːk/", "tags": [ "UK" ] }, { "ipa": "/ˈbeɪ.zjən ˈnɛt.wɝk/", "tags": [ "US" ] } ], "word": "Bayesian network" }
{ "etymology_text": "Named after Thomas Bayes (1701–1761), English mathematician.", "forms": [ { "form": "Bayesian networks", "tags": [ "plural" ] } ], "head_templates": [ { "args": {}, "expansion": "Bayesian network (plural Bayesian networks)", "name": "en-noun" } ], "hypernyms": [ { "word": "graphical model" }, { "word": "probabilistic graphical model" } ], "lang": "English", "lang_code": "en", "pos": "noun", "senses": [ { "categories": [ "English countable nouns", "English entries with incorrect language header", "English eponyms", "English lemmas", "English multiword terms", "English nouns", "Pages with 1 entry", "Pages with entries", "en:Statistics" ], "glosses": [ "A directed acyclic graph whose vertices represent random variables and whose directed edges represent conditional dependencies. Each random variable can fall into any of at least two mutually disjoint states, and has a probability function which takes as inputs the states of its parent nodes and returns as output the probability of being in a certain state for a given combination of the states of its parent nodes. A node without parent nodes just has an unconditioned probability of being in some given state." ], "links": [ [ "statistics", "statistics" ], [ "random variable", "random variable" ], [ "conditional", "conditional probability" ] ], "raw_glosses": [ "(statistics) A directed acyclic graph whose vertices represent random variables and whose directed edges represent conditional dependencies. Each random variable can fall into any of at least two mutually disjoint states, and has a probability function which takes as inputs the states of its parent nodes and returns as output the probability of being in a certain state for a given combination of the states of its parent nodes. A node without parent nodes just has an unconditioned probability of being in some given state." ], "topics": [ "mathematics", "sciences", "statistics" ], "wikipedia": [ "Bayesian network", "Thomas Bayes" ] } ], "sounds": [ { "ipa": "/ˈbeɪ.zjən ˈnɛt.wɜːk/", "tags": [ "UK" ] }, { "ipa": "/ˈbeɪ.zjən ˈnɛt.wɝk/", "tags": [ "US" ] } ], "word": "Bayesian network" }
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This page is a part of the kaikki.org machine-readable All languages combined dictionary. This dictionary is based on structured data extracted on 2024-12-21 from the enwiktionary dump dated 2024-12-04 using wiktextract (d8cb2f3 and 4e554ae). The data shown on this site has been post-processed and various details (e.g., extra categories) removed, some information disambiguated, and additional data merged from other sources. See the raw data download page for the unprocessed wiktextract data.
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