Patent ID: 11893463
Assignee: THROUGHPUTER, INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 10:
11. A hierarchical estimator comprising:
an array of object models stored in a non-transitory digital memory, wherein
the array of object models is organized into a plurality of model banks, with one or more given model banks of the plurality of model banks comprising a respective subset of the object models that are related by a respective common object classification of a plurality of classifications, such respective common object classification corresponding to an identification of at least one defined value and/or value range for a qualitative or quantitative attribute that denotes the object models of that classification;
first estimator stage logic, configured to identify, for an input object having at least one latent feature to be estimated, one or more candidate classifications from the plurality of classifications;
second estimator stage logic, configured to apply the object models from one or more selected banks of the plurality of model banks to the input object, the selection of the one or more selected banks for the input object based on the one or more candidate classifications identified for the input object by the first estimator stage logic, wherein for at least one given bank of the one or more selected banks, applying the object models from that given bank comprises identifying a set of one or more closest matching models to the input object;
output logic, configured to generate, based on the identification of the set of one or more closest matching models for at least one of the one or more selected banks, an estimated value for the at least one latent feature; and
model update logic, configured to, in realtime and in response to receipt of a training object, update a target object model corresponding to the training object;
wherein the hierarchical estimator is configured to perform interleaved processing of input objects having at least one feature to be estimated and training objects.