Naïve Bayes

Christo El Morr, Manar Jammal, Hossam Ali-Hassan and Walid El-Hallak ()
Additional contact information
Christo El Morr: York University
Manar Jammal: York University
Hossam Ali-Hassan: York University, Glendon Campus
Walid El-Hallak: Ontario Health

Chapter Chapter 9 in Machine Learning for Practical Decision Making, 2022, pp 279-299 from Springer

Abstract: Abstract So far, during classification, we have been interested in finding a model that decides if an instance belongs to a class or not; the model’s answer would be a yes or no with certainty. The situation with Bayesian modeling for decision-making is different—it estimates the probability that an instance belongs to a certain class, which is more nuanced [1].

Date: 2022
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:isochp:978-3-031-16990-8_9

Ordering information: This item can be ordered from
http://www.springer.com/9783031169908

DOI: 10.1007/978-3-031-16990-8_9

Access Statistics for this chapter

More chapters in International Series in Operations Research & Management Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().