10 июл. 2024 г. · Naive Bayes classifiers are a collection of classification algorithms based on Bayes' Theorem. It is not a single algorithm but a family of algorithms.

Naïve Bayes algorithm is a supervised learning algorithm, which is based on Bayes theorem and used for solving classification problems.

Naive Bayes Algorithm is a classification method that uses Bayes Theory. It assumes the presence of a specific attribute in a class.

Naive Bayes methods are a set of supervised learning algorithms based on applying Bayes' theorem with the “naive” assumption of conditional independence.

The Naïve Bayes classifier is a supervised machine learning algorithm that is used for classification tasks such as text classification.

Naive Bayes classifiers are a family of linear probabilistic classifiers which assumes that the features are conditionally independent, given the target class.

Naive Bayes is a statistical classification technique based on Bayes Theorem. It is one of the simplest supervised learning algorithms.

29 июн. 2023 г. · The naïve Bayes algorithm is a family of probabilistic classification algorithms used for tasks like text classification, ...

The Naive Bayes algorithm is a classification algorithm based on Bayes rule and a set of conditional independence assumptions. Given the goal of learning P(Y|X).

Naïve Bayes is a probabilistic machine learning algorithm based on the Bayes Theorem, used in a wide variety of classification tasks.