The term "learning classifier system" most often refers to Michigan-style LCSs.

Derbyshire & Payne (1990) list three basic types of classifier systems.

Gender systems rarely overlap with numerical classifier systems.

Khasi has a classifier system, apparently used only with numerals.

So we have to make do with still-unfamiliar terms like genetic algorithms, artificial life, classifier systems and neural networks.

Many languages close to Chinese exhibit similar classifier systems, leading to speculation about the origins of the Chinese system.

As a whole, though, the classifier system is so complex that specialized classifier dictionaries have been published.

In research on classifier systems, and Chinese classifiers in particular, it has been asked why count-classifiers (as opposed to mass-classifiers) exist at all.

Other approaches using meta-data to improve automatic learning are learning classifier systems, case-based reasoning and constraint satisfaction.

The broader term of multiple classifier systems also covers hybridization of hypotheses that are not induced by the same base learner.