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The role of decision tree representation in regression problems – An evolutionary perspective
2016
Applied Soft Computing
A regression tree is a type of decision tree that can be applied to solve regression problems. One of its characteristics is that it may have at least four different node representations; internal nodes can be associated with univariate or oblique tests, whereas the leaves can be linked with simple constant predictions or multivariate regression models. The objective of this paper is to demonstrate the impact of particular representations on the induced decision trees. As it is difficult if not
doi:10.1016/j.asoc.2016.07.007
fatcat:2o6f4ywgtrf6pcmipqju35xyiy