Learning Data Mining with Python - Second Edition

Implementing a simple ranking of rules

We wish to find rules of the type If a person buys product X, then they are likely to purchase product Y. We can quite easily create a list of all the rules in our dataset by simply finding all occasions when two products are purchased together. However, we then need a way to determine good rules from bad ones allowing us to choose specific products to recommend.

We can evaluate rules of this type in many ways, on which we will focus on two: support and confidence.

Support is the number of times that a rule occurs in a dataset, which is computed by simply counting the number of samples for which the rule is valid. It can sometimes be normalized by dividing by the total number of times the premise of ...