Glossary

A Naive Bayes Classifier is an efficient supervised learning model in machine learning that uses Bayes’ theorem to predict an object’s category based on its features. It requires a training dataset to determine class probabilities and uses these to categorize new instances.

Naive Semantics is a straightforward method for interpreting the meaning of words or phrases based solely on their apparent form, exempting in-depth linguistic or conceptual connections.

In programming, Name Binding is the crucial process that links entities such as data and code to specific identifiers. Scopes guide this process by determining the applicable object for each name within program locations.