What Does Naive Bayes Mean?
A naive Bayes classifier is an algorithm that uses Bayes’ theorem to classify objects. Naive Bayes classifiers assume strong, or naive, independence between attributes of data points. Popular uses of naive Bayes classifiers include spam filters, text analysis and medical diagnosis. These classifiers are widely used for machine learning because they are simple to implement.
Techopedia Explains Naive Bayes
A naive Bayes classifier uses probability theory to classify data. Naive Bayes classifier algorithms make use of Bayes’ theorem. The key insight of Bayes’ theorem is that the probability of an event can be adjusted as new data is introduced.
