Supervised Learning: Classification
OBJECTIVE OF THE CHAPTER :
In the last chapter on Bayesian Concept Learning, you were introduced to an important supervised learning algorithm – the Naïve Bayes algorithm. As we have seen, it is a very simple but powerful classifier based on Bayes’ theorem of conditional probability. However, other than the Naïve Bayes classifier, there are more algorithms for classification. This chapter will focus on other classification algorithms.
The first algorithm we will delve into in this chapter is k-Nearest Neighbour (kNN), which tries to classify unlabelled data instances based on the similarity with the labelled instances in the training data.
Then, another critical classifier, named ...