naive Bayes classifier

6.2

A simple method that uses chance to put items into groups, assuming each detail acts alone

noun
/naɪv beɪz ˈklæɪsɪfaɪər/

Specialized

: clasificador de Bayes ingenuo

The naive Bayes classifier performed surprisingly well on the spam detection task.

Examples

Using a naive Bayes classifier requires the assumption that the features are independent given the class label.
Many introductory machine learning courses teach the naive Bayes classifier due to its simplicity and effectiveness.
The naive Bayes classifier is widely used in text classification.
Many data scientists prefer the naive Bayes classifier for spam detection.
The Naive Bayes classifier is often used for spam detection in email applications.
Researchers utilized a Naive Bayes classifier to analyze the sentiment of customer reviews.
In machine learning, a Naive Bayes classifier can effectively handle large datasets with many features.

Surface Forms

naive Bayes classifier singular

naive Bayes classifiers plural

Morphology

naive + Bayes + classifier

A B1 learner who knows 'naive' and 'classifier' could reasonably infer 'a simple classifier', but they will not be able to derive the technical meaning that it is a probabilistic model based on Bayes' theorem with an independence assumption because 'Bayes' is a proper name referring to a specific statistical principle. Part of the sense is compositional (simple classifier) but the crucial probabilistic/Bayes-specific aspect is technical and requires prior exposure, so the expression is only partially transparent.

Etymology

Naive Bayes classifier is named for Bayes, the thinker behind a simple math rule, and for the word naive, which points to its simple idea: the model treats each feature as if it stands alone and does not affect the others. So the name helps you remember that this method uses Bayes' rule to sort things into groups while making a simple 'each part stands alone' assumption.