Competitive learning in decision trees
Dominique Martinez · AIP conference proceedings · 1998
In this paper, a competitive learning rule is introduced in decision trees as a computationally attractive scheme for adaptive density estimation or lossy compression. It is shown by simulation that the adaptive decision tree performs at least as well as other competitive learning algorithms while being much faster.