The Naïve Bayes classifier is a probabilistic algorithm used in Machine Learning for classification tasks based on Bayes’ theorem. It assumes that features are independent of each other, which simplifies computation and makes it efficient for large datasets. This model is widely used in applications like spam detection, text classification, and sentiment analysis. Despite its simplicity, it often performs well in real-world scenarios with high-dimensional data.
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