4 Naive Bayes

1. Naive bayes is a supervised learning algorithm for classification so the task is to find the class of observation (data point) given the values of features. Naive bayes classifier calculates the probability of a class given a set of feature values (i.e. p(yi | x1, x2 , … , xn)).

1.1. https://www.geeksforgeeks.org/naive-bayes-classifiers/ https://medium.datadriveninvestor.com/data-science-naive-bayes-classifications-1044a71e21c2 https://towardsdatascience.com/all-about-naive-bayes-8e13cef044cf https://towardsdatascience.com/naive-bayes-classifier-explained-50f9723571ed https://www.analyticsvidhya.com/blog/2021/09/naive-bayes-algorithm-a-complete-guide-for-data-science-enthusiasts/ https://medium.com/the-data-science-publication/how-to-predict-natural-language-sentiment-using-naive-bayes-classifier-6ab6eb28fd6d https://www.kdnuggets.com/2020/06/naive-bayes-algorithm-everything.html https://jakevdp.github.io/PythonDataScienceHandbook/05.05-naive-bayes.html https://pub.towardsai.net/naive-bayes-classifier-in-machine-learning-b0201684607c https://devopedia.org/naive-bayes-classifier

2. Naive Bayes classifier assumes that the presence of a particular feature/variable in a class is unrelated (independent) to the presence of any other feature.