Naive Bayes is one of the simplest classification machine learning algorithm. As the name suggests its based on the Bayes theorem.
Doing my thesis using Probabilistic Programming I always had read about many models and how it compared with Naive Bayes classifier. Even though of the simplicity Naive bayes is a pretty solid and basic classifier every machine learning student should know. But I never had an opportunity to fully understand this simple tool mainly because I used it like a blackbox using many implementations available, the most famous being from scikit learn
There is a lot of ink spent on the topic by most prominent scholars of all time so I really dont want to add anything to the debate.
The 1 paper which influenced me in getting a practical overview of the topic and showing tangiblly was by Jake Vanderplass , where he explains with 2 examples
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