Summary

In this chapter, we discussed some advanced algorithms in ML and found out how to use a simple yet powerful method of Bayesian inference to build another kind of classification model, multinomial classification algorithms. Moreover, the Naive Bayes algorithm was discussed broadly from the theoretical and technical perspectives. At the last pace, a comparative analysis between the DT and Naive Bayes algorithms was discussed and a few guidelines were provided.

In the next chapter, we will dig even deeper into ML and find out how we can take advantage of ML to cluster records belonging to a dataset of unsupervised observations.