Machine Learning Quick Reference

Finding association rules

In order to find the association rules, we have to first search for all of the rules that have support greater than the threshold support. But the question arises: how do we find these? A possible way to find this is by brute force, which means to list all the possible association rules and calculate the support and confidence for each rule. Later, remove all the rules that fail the confidence and support thresholds.

Given there are n items in the set I, the total number of possible association rules is 3ⁿ - 2ⁿ⁺¹ + 1.

If X is a frequent itemset with k elements, then there are 2^k - 2 association rules.

Let's see how to execute association rules in Python:

import numpy as npimport matplotlib.pyplot as pltimport pandas ...