This chapter explains the regression and classification technique in machine learning and its implementation using different machine learning algorithms in Apache Mahout. The machine learning theory behind the algorithm and real-world applications with example scripts are also explained.
In this chapter, we will cover the following topics:
Supervised learning
Target variables and predictor variables
Predictive analytics techniques
Classification versus regression
Linear regression with Apache Spark
Logistic regression with Stochastic Gradient Descent (SGD)
Naïve Bayes algorithm
Hidden Markov Models (HMMs)