Naive Bayes Classifier Tutorial | Naive Bayes Demo | Machine Learning Algorithm | Great Learning

A Naïve 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 Naïve Bayes classifiers include spam filters, text analysis and medical diagnosis. These classifiers are widely used for machine learning because they are simple to implement. This theorem is the foundation of deductive reasoning, which focuses on determining the probability of an event occurring based on prior