In data mining, a treatment learner is a program used to find rules that change the expected class distribution (compared to some baseline). A classifier is a treatment learned used for recognition tasks, such as identifying defective items in an assembly line. Treatment learners include the J48, J48part, and APRIORI for discrete classes, TAR2 and TAR3 for weighted discrete classes, and the M5 for continuous classes. Treatment learners are all about minimality - what is the least you need to do to most effect something.