Association rule learning is a method for finding relationships between variables in large datasets. It is frequently used in market basket analysis, but its applications extend to various fields including nanotechnology. The core objective is to identify rules that describe how the presence of one item or event is related to the presence of another. The rules are typically expressed in the form: If A, then B, where A and B are items or sets of items.
