Patent ID: 6810368
Filing Date: 2004-10-26
Classification: G06F

Abstract:
A program storage device readable by a machine, tangibly embodying a program of instructions executable by the machine to perform method steps for constructing a predictive model that can be used to make predictions even when the values of some or all inputs are missing or are otherwise unknown, the method comprising:(1) presenting a collection of training data comprising examples of input values that are available to the model together with corresponding desired output value(s) that the model is intended to predict; (2) generating a plurality of subordinate models, that together comprise an overall model, in such a way that: a) each subordinate model has an associated set of application conditions that must be satisfied in order to apply the subordinate model when making predictions, the application conditions comprising: i) tests for missing values for all, some, or none of the inputs, and ii) tests on the values of all, some, or none of the inputs that are applicable when the values of the inputs mentioned in the tests have known values; and b) for at least one subordinate model, the training cases used in the construction of that subordinate model include some cases that indirectly satisfy the application conditions such that the application conditions are satisfied only after replacing one or more known data values in these training cases with missing values; and 3) outputting a specification of at least one of said subordinate models thus generated and making a prediction based on said at least one of said subordinate models thus-generated.