Resumen de Testing Modified Confusion Entropy as Split Criterion for Decision Trees

José David Núñez González, Alexander Gonzalo de Sá, Manuel Graña Romay

• Confusion Entropy (CEN) has been proposed as a performance measure for classification showing a better discrimination against other metrics. Many works use CEN for other purposes. Recently, an improvement in the definition of CEN has been proposed, a modified CEN (MCEN). The aim of this work is to review a previous work based on a classification tree that uses CEN as a pruning criterion, replacing this criterion with the newly defined MCEN metric.