Evolving the input space for decision tree building

The aim of this research is to extend the discrimination of a decision tree builder by adding polynomials of the base inputs to the inputs. The polynomials used to extend the inputs are evolved using the quality of the decision trees resulting from the extended inputs as a fitness function. Our approach generates a decision tree using the base inputs and compares it with a decision tree built using the extended input space. Results show substantial improvements.