Classification
Vijay Kotu, Bala Deshpande · Data Science · 2019
In classification or class prediction, it’s best to try to use the information from the predictors or independent variables to sort a data sample into two or more distinct classes or buckets. Classification is the most widely used data science task in business. There are several ways to build classification models. In this chapter, six of the most commonly used classification algorithms will be discussed and demonstrated: decision trees, rule induction, k -nearest neighbors ( k -NNs), naïve Bayesian, artificial neural networks, and support vector machines. This chapter is concluded by building ensemble classification models and a discussion on bagging, boosting, and random forests.