Naive Bayes classifier
id:
naive-bayes-classifier-185-17780633
title:
Naive Bayes classifier
text:
In statistics, naive Bayes classifiers are a family of linear "probabilistic classifiers" which assumes that the features are conditionally independent, given the target class. The strength (naivety) of this assumption is what gives the classifier its name. These classifiers are among the simplest Bayesian network models. Naive Bayes classifiers are highly scalable, requiring a number of parameters linear in the number of variables (features/predictors) in a learning problem. Maximum-likelihood
brand slug:
wiki
category slug:
encyclopedia
description:
Probabilistic classification algorithm
original url:
https://en.wikipedia.org/wiki/Naive_Bayes_classifier
date created:
2002-09-18T18:29:12Z
date modified:
2024-09-07T21:05:25Z
main entity:
{"identifier":"Q812530","url":"https://www.wikidata.org/entity/Q812530"}
image:
{"content_url":"https://upload.wikimedia.org/wikipedia/commons/d/de/Naive_corral.png","width":647,"height":518}
fields total:
13
integrity:
16