Patent ID: 8521659

Claim:
A method, implemented in a computer readable and executable program on a computer processor, of discovering mixtures of models within data and probabilistic classification of data according to model mixtures, the method comprising: receiving, a request for discovering mixtures of models within data and probabilistic classification of data according to model mixtures; initiating a learning algorithm, by the computer processor, causing the computer processor to execute the computer readable and executable program for simultaneously discovering mixtures of models within data and probabilistic classification of data according to mixture models of a plurality of models; applying a random sampling operation to determine mathematical functions; determining multiple models of the plurality of models that fit portions of mixture models of the plurality of models; probabilistically assigning points to multiple models of the plurality of models by using abstractions of mathematical functions to form simulated equivalent mathematical functions, causing one or more mathematical functions to be processed as one or more of the plurality of models; comparing multiple models of the plurality of models by comparing different mathematical functions and by comparing a first quality of a first model to a second quality of a second model, wherein a number of points supporting an at least one candidate model are counted to determine whether sufficient data are modeled, wherein global accounting ensures that the number of points supporting the at least one candidate model are only counted once, when determining how many of the number of points in data are modeled by candidate functions, and wherein comparing different mathematical functions includes using geometric properties, including overlap, the number of points supporting the at least one candidate model counted, and density; and providing user settable thresholds for user interaction with computations of residual error and with computations of the number of points supporting the at least one candidate model corresponding to learned mixture models.