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.
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