Learning prototype-based classifiers by margin maximization

We study classifiers based on prototypes, which classify data points by the nearest neighbor rule, namely a data point is labeled the class which has its nearest prototype. The prototype-based classifiers are trained by the max-margin principle, which is used by support vector machines. For each tra... View More