1. A method for selecting clusterings to classify a predetermined numerical data set, the method implemented in a data processor having a memory and a display and comprising: (a) using the data processor to sequentially apply a plurality of clustering methods to the numerical data set to generate a plurality of clusterings and storing the clusterings in the memory; (b) using the data processor and a metric that measures a similarity between two clusterings generated by a pair of the clustering methods to create a metric space of clusterings in the memory; (c) using the data processor to project the metric space to a lower dimensional space of clusterings; (d) using the data processor to generate at each point in the lower dimensional space which does not represent a clustering, a clustering for that point based on nearby clusterings; and (e) displaying points representing the lower dimensional space on the display.