Novel data condensing method using a prototypes front propagation algorithm

This work proposes a method for data condensing. The method is based on the selection of a generator of data prototypes. An algorithm for the front propagation of the prototypes boundaries is performed in order to obtain the class boundaries given by a set of support vectors. The proposed method just has one tuning parameter and presents high classification rates even for complex topological and non-concave classes and low tendency to over-fitting. The most important advantage of the proposed method is its higher condensing rate without a significant detrimental effect on the classification rate. The algorithm is intended to be applied for condensing data in low memory devices and transmission of high-volume of data where data condensing could be crucial.