Patent ID: 8392153

Claim:
A method for a process performed on a computer for training multivariate segment model objects, the method comprising: 1) accessing a collection of training data records comprising examples of input values that are available to a multivariate segment model object, together with corresponding desired output value(s) that a multivariate segment model is intended to predict; 2) presenting, as executed by a processor on a computer, the training data records to the multivariate segment model object by calling one or more scan-data-record interface functions, wherein the multivariate segment model object responds by generating and pruning pluralities of data segments and associated segment models, at least one of which comprises a training-data-based multivariate segment model for the multivariant segment model; and 3) repeating said accessing and said presenting until the multivariate segment model object indicates that it does not need to have the training records presented over again, as determined by calculating whether a predictive accuracy of the data segments and associated segment models is optimal, based on an evaluation using validation data records different from said training data records.