Improving induction of linear classification trees with genetic programming
Martijn C. J. Bot · 2000
A common problem in datamining is to find accurate classifiers for a dataset. For this purpose, genetic programming (GP) is applied to a set of benchmark classification problems. Using GP, we are able to induce decision trees with a linear combination of variables in each function node.