| CPC G06N 20/00 (2019.01) [G06F 16/23 (2019.01); G06F 16/24568 (2019.01); G06F 16/9017 (2019.01); G06F 18/214 (2023.01); G06F 18/2411 (2023.01)] | 21 Claims |
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1. A method for estimating values of unknown features of a series of objects, the objects being represented as digital feature vectors, each respective digital feature vector including a plurality of X-variables having corresponding values populated on the respective digital feature vector before the estimating as a plurality of received X-variables, and, for at least a portion of the series of objects, a Y-variable having an unknown value prior to the estimating, the method comprising operations performed by a hierarchical estimator, the hierarchical estimator comprising hardware logic configured to perform at least a portion of the operations and/or software logic stored on a non-transitory digital medium and configured to perform, when executing via processing circuitry, at least a portion of the operations, the operations comprising:
maintaining, by the hierarchical estimator on a non-transitory digital memory, an array of object models, wherein
each model of the array of object models comprises at least a partial Y-variable value and a plurality of X-variable values corresponding to the respective at least a partial Y-variable value, and
the array of object models is organized as a plurality of banks, with at least one given bank comprising a respective subset of the object models that are related by a respective common object classification of a plurality of classifications, wherein such classification corresponds to an identification of at least one defined value and/or value range for a qualitative or quantitative attribute that characterizes the respective subset of the object models of that classification according to the at least a partial Y-variable values of the respective subset of the object models;
for each respective input object of at least a portion of the series of objects, in realtime,
in a first stage of the hierarchical estimator, determining, for the respective input object, one or more candidate classifications from the plurality of classifications,
in a second stage of the hierarchical estimator,
for each of one or more given banks related to one of the one or more candidate classifications, identifying, from the object models in that given bank, a set of one or more closest matching models for the respective input object, and
producing an estimated value of the Y-variable of the input object based at least in part on a Y-variable value of one or more models of the set of closest matching models for at least one of the banks associated with at least one of the one or more candidate classifications; and
for given training objects of a series of training objects received interspersed in time with receipt of the input objects in the series of objects,
updating a target object model from the array of object models, and corresponding to each given training object, in realtime.
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