Naive Bayes

Naive Bayes is a statistical method used for classification, based on applying Bayes' theorem with the assumption that features are independent given the class. It calculates the probability that a data point belongs to a specific category by considering how likely each feature value is for that category and combining these probabilities. Despite the simplification of assuming features are independent, it often performs well in real-world tasks like spam detection or document classification, making predictions efficiently and effectively by leveraging probabilities derived from training data.