Associations

Associations are the specific measurable constraints on interestingness used in association rule learning. Regardless of the rules being employed to classify new data, the associations need to be defined by constraints to determine what is both interesting and relevant. Support – How frequently the pattern/items occur in the dataset. Confidence – How often the rule being used has been true (conditional probability). Lift – Actual success rate of the target model (rule) over the expected success from random chance.