Chapter 4. Classification with Mahout
One of the most widely used tasks in machine learning is to predict discrete outcomes or classes of future data instances, using historical data. It is a very popular branch of supervised learning, and a wide variety of problems can be solved using this paradigm. Questions such as whether to approve a loan to someone or determining the probability of a telecom subscriber not renewing the contract can be answered using classification algorithms. In this chapter, we are going to discuss some of the important classification algorithms in Mahout. We will learn about the following classification algorithms:
Logistic regression
Random forest
naïve Bayes