STABLE DECISION TREES: USING LOCAL ANARCHY FOR EFFICIENT INCREMENTAL LEARNING
Dimitris Kalles, Athanasios Papagelis · International Journal of Artificial Intelligence Tools · 2000
This work deals with stability in incremental induction of decision trees. Stability problems arise when an induction algorithm must revise a decision tree very often and oscillations between similar concepts decrease learning speed. We introduce a heuristic and an algorithm with theoretical and experimental backing to tackle this problem.