4. The article of claim 1 , further comprising: iterating through all objects exactly once at each temperature.
1. An article comprising a non-transitory machine-readable storage medium operable to cause one or more machines to result in operations comprising: arranging objects which are realizations of a first variable and a second variable into a current clustering to aid in solving a problem; constructing a shortlist of destination clusters, the shortlist containing a predetermined number, N, of destination clusters for a current object, each destination cluster associated with a score, each destination cluster in the shortlist having an associated score that is greater than an associated score of each destination cluster not in the shortlist; picking randomly a destination cluster from said shortlist of destination clusters; determining if said picked destination cluster is acceptable according to a probabilistic acceptance criteria at a current temperature, T, the current temperature representing an iteration of temperature out of a plurality of iterations of temperature from a first temperature to a second temperature; replacing said current clustering with said picked destination clustering, if said picked destination clustering is acceptable; repeating, at each iteration of temperature, the picking, the determining, and the replacing until no acceptable destination clusters from said shortlist of destination clusters remain; establishing said current clustering of objects as an output clustering, wherein said output clustering has a high confidence level of having a maximum of mutual information between said variables for predicting relationships between said variables; and outputting said output clustering for display to a user for use in solving said problem based on maximally predictive feature sets.