Chapter 3. Regression and Classification
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)
