Data Set Selection

We introduce the community to a new construction principle whose practical implications are very broad. Central to this research is the idea of improving the presentation of algorithms in the literature and making them more appealing. We define a new notion of capacity for data sets and derive a methodology for selecting from them. Our experiments demonstrate that even not-so-good algorithms can be shown significantly better than competitors. We present some experimental results, which are very promising.