Bayesian approaches
[BAY-zhən ə-PROH-chez / bai-ˈzi-ən]
nounpl: Bayesian approaches
abordagens bayesianas
1. Statistical methods based on Bayes' theorem that use prior knowledge or beliefs combined with observed data to calculate posterior probabilities and make inferences
Bayesian approaches have become increasingly popular in machine learning and data science.
As abordagens bayesianas tornaram-se cada vez mais populares em aprendizado de máquina e ciência de dados.
2. A framework for statistical analysis that treats probability as a measure of belief or certainty rather than just frequency of occurrence
Bayesian approaches allow researchers to incorporate prior information into their statistical models.
As abordagens bayesianas permitem que pesquisadores incorporem informações anteriores em seus modelos estatísticos.
Bayesian approaches represent a paradigm shift in statistics and data science, particularly embraced in Silicon Valley and tech-driven research communities. In Brazil and Portugal, the terminology is primarily used in academic, research, and technology sectors. The approach contrasts with frequentist methods that dominated 20th-century statistics, and is increasingly taught in universities as computational power makes Bayesian methods more practical.
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