Practical Machine Learning

Summary

In this chapter, you have learned the association rule based learning methods and, Apriori and FP-growth algorithms. With a common example, you learned how to do frequent pattern mining using Apriori and FP-growth algorithms with a step-by-step debugging of the algorithm. We also compared and contrasted the algorithms and their performance. We have example implementations for Apriori using Mahout, R, Python, Julia, and Spark. In the next chapter, we will cover the Bayesian methods and specifically, the Naïve-Bayes algorithm.