Editing Decision tree (section)

== Association rule induction ==
{{main|Decision tree learning}}
Decision trees can also be seen as [[generative model]]s of induction rules from empirical data. An optimal decision tree is then defined as a tree that accounts for most of the data, while minimizing the number of levels (or "questions").<ref>R. Quinlan, [https://link.springer.com/chapter/10.1007%2F978-3-662-12405-5_15#page-1 "Learning efficient classification procedures"], ''Machine Learning:  an artificial intelligence approach'', Michalski, Carbonell & Mitchell (eds.), Morgan Kaufmann, 1983, p. 463–482.  {{doi|10.1007/978-3-662-12405-5_15}}</ref> Several algorithms to generate such optimal trees have been devised, such as [[ID3 algorithm|ID3]]/4/5,<ref>Utgoff, P. E. (1989). Incremental induction of decision trees. Machine learning, 4(2), 161–186.  {{doi|10.1023/A:1022699900025}}</ref> CLS, ASSISTANT, and CART.