Existing classification procedures fail to uncover the predictive structure of classification problems, which is key to taking actions. This work suggests a new approach for finding highly actionable rules, using existing association rules mining algorithms, to explain the occurrence of events in mixed high-dimensional manufacturing data. Solutions to several limitations to association rules mining from process data are addressed and a new methodology for organizing and grouping the association rules with the same consequent is provided. Supervised association rules mining from a...