1. A computer-implemented method for efficiently processing a large number of records, the method comprising: estimating, by a computer system, a probability that subject data is in a single class by: obtaining, by the computer system, a plurality of records, the plurality of records comprising the subject data; obtaining, by the computer system, two or more probability estimation trees, each of the two or more probability estimation trees comprising multiple paths; processing, by the computer system, the plurality of records through at least two of the two or more probability estimation trees the processing in each of the at least two of the two or more probability estimation trees comprising: arriving of the subject data, at a distinction node of the each of the at least two of the two or more probability estimation trees, the distinction node corresponding to a distinction requiring completion of an as yet uncomputed computation; completing, by the computer system after the arriving of the subject data at the distinction node of the each of the at least two of the two or more probability estimation trees, the computation; making the distinction based on results of the computation; selecting a path of the multiple paths based at least in part on the distinction; directing the subject data to another distinction node of the each of the at least two of the two or more probability estimation trees; and estimating a class for the subject data based at least in part on the path of the multiple paths selected; and combining, by the computer system, the class that is estimated of the at least two of the two or more probability estimation trees into the single class.