Naive Bayes

Here you’ll find everything about Naive Bayes, whether it’s Python tutorials on how to implement the algorithm or conceptual articles explaining how it works.

Naive Bayes is a probabilistic machine learning algorithm that is based on Bayes’ theorem. It is called “naive” because it makes the assumption that the features in a dataset are independent of each other, which is not always true in real-world data. Despite this assumption, naive Bayes algorithms are often effective for classification tasks and are particularly well-suited for text classification.