Controlled Flux Results in Stable Decision Trees

Authors:
Dimitrios Kalles;Athanassios Papagelis
Affiliations:
-;-
Venue:
ICTAI '99 Proceedings of the 11th IEEE International Conference on Tools with Artificial Intelligence
Year:
1999

Citing 8
Cited 0

Incremental induction of topologically minimal trees

Proceedings of the seventh international conference (1990) on Machine learning
Technical Note: Bias and the Quantification of Stability

Machine Learning - Special issue on bias evaluation and selection
Efficient incremental induction of decision trees

Machine Learning
Incremental Induction of Decision Trees

Machine Learning
Induction of Decision Trees

Machine Learning
The Effects of Training Set Size on Decision Tree Complexity

ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Decision tree grafting

IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
What should be minimized in a decision tree?

AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 2

Quantified Score

Hi-index	0.00

Visualization

Abstract

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.