Rok Piltaver: Generating accurate AND understandable hybrid classification trees

Most algorithms that induce classifiers primarily aim for high accuracy while they take understandability into account as a secondary measure of classifier's quality. The algorithm that will be presented efficiently generates a range of hybrid classification trees ranging from the most understandable to the most accurate ones by combining an easy to understand decision tree with a black-box classifier with a high accuracy. That enables the user to choose how much of accuracy he/she is willing to sacrifice for a higher understandability or vice versa.


Thursday, 13.1.2011, 13:00, Orange room