Association rule inference consists on generating rules that batch together items that are typically batched together out of several different item sets. ## Metrics There are different metrics that are used to evaluate the rules generated, as per [[mlxtend]] documentation: ![[Support of an Item Set]] ![[Confidence of an Association Rule]] ![[Lift of an Association Rule]] ![[Leverage of an Association Rule]] ![[Conviction of an Association Rule]] ![[Zhang's Metric for Association Rules]] ## Algorithms ![[Apriori]] ![[FP-Growth]] ![[FP-Max]]