In this paper we propose the acquisition of a set of preferences of collaboration between classifiers based on decision trees. A classifier uses a well-known algorithm (k-NN with leaf-one-out) on its own knowledge base to generate a set of tuples with information about the object to be classified, the number of similar precedents, the maximum similarity, and about if it is a situation of collaboration or not. We considered that a classifier does not collaborate when it is able to reach by itself the correct classification for an object, otherwise it has to collaborate. The mentioned set of tuples is given as input to generate a decision tree from which a set of collaboration preferences is obtained.

The author also acknowledges support by the Spanish MICINN projects EdeTRI (TIN2012-39348-C02-01) and COGNITIO (TIN2012-38450-C03-03) and the grant 2014SGR-118 from the Generalitat de Catalunya.

Peer Reviewed