Machine Learning with R Cookbook - Second Edition

How it works...

The purpose of association mining is to discover associations among items from the transactional database. Typically, the process of association mining proceeds by finding itemsets that have support greater than the minimum support. Next, the process uses the frequent itemsets to generate strong rules (for example, milk => bread a customer who buys milk is likely to buy bread) that have confidence greater than minimum confidence. By definition, an association rule can be expressed in the form of X=>Y, where X and Y are disjointed itemsets. We can measure the strength of associations between two terms: support and confidence. Support shows how much of the percentage of a rule is applicable within a dataset, while confidence ...