Online trained object property estimator
AssigneeThroughPuter, Inc.
InventorMark Henrik Sandstrom
Life of this patent
Estimating the term…
Abstract
This disclosure describes systems and methods for using an estimator to produce values for dependent variables of streaming objects based on values of independent variables of the objects. The systems and methods may include continuously tuning the estimator based on any objects received with pre-populated values for the dependent variables.
Claims20
A method for estimating values of unknown features of a series of objects, the objects being represented as digital feature vectors, at least some of such digital feature vectors including a plurality of X variables having corresponding values populated on the respective digital feature vector before the estimating as a plurality of populated 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 an estimator, the estimator comprising hardware logic and/or software logic executing via processing circuitry, the operations comprising:
- maintaining, by the estimator on a non-transitory digital memory, an array of models, wherein
- each model of the array of models comprises a Y-variable value and a plurality of X-variable values corresponding to the respective Y-variable value, and
- the array of models is organized according to Y-variable values of the models;
- and
- for each object of at least a portion of the series of objects,
- computing, by the estimator, an estimated value of the Y-variable of the respective object by identifying, from the array of models, a set of closest matching models based on a measure of difference between the values of at least a subset of the X-variables of the respective object and a corresponding subset of the X-variable values of at least a portion of the models of the array of models, and
- producing the estimated value of the Y-variable of the respective object based at least in part on a Y-variable value of one or more models of the set of closest matching models,
- wherein said maintaining includes:
- ascertaining and populating an actual value corresponding to the estimated value of the Y-variable of the respective object to make it a training object,
- as a real-time operation interleaved with the estimating values of the unknown features of the series of objects, inserting the training object within the series of objects, and
- updating a model of the array of models corresponding to the Y-variable value of the training object, based at least in part on the X-variable values of the training object and of existing X-variable values of the model.
A system for estimating values of unknown features of a series of objects, the objects being represented as digital feature vectors, at least some of such digital feature vectors including a plurality of X variables having corresponding values populated on the respective digital feature vector before the estimating as a plurality of populated 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 system comprising an estimator comprising hardware logic and/or software logic stored on a non-transitory digital medium and configured for execution via processing circuitry, the estimator performing operations comprising:
- maintaining, by the estimator on a non-transitory digital memory, an array of models, wherein
- each model of the array of models comprises a Y-variable value and a plurality of X-variable values corresponding to the respective Y-variable value, and
- the array of models is organized according to Y-variable values of the models;
- and
- for each object of at least a portion of the series of objects,
- computing, by the estimator, an estimated value of the Y-variable of the respective object by identifying, from the array of models, a set of closest matching models based on a measure of difference between the values of at least a subset of the X-variables of the respective object and a corresponding subset of the X-variable values of at least a portion of the models of the array of models, and
- producing the estimated value of the Y-variable of the respective object based at least in part on a Y-variable value of one or more models of the set of closest matching models,
- wherein said maintaining includes:
- ascertaining and populating an actual value corresponding to the estimated value of the Y-variable of the respective object to make it a training object,
- as a real-time operation interleaved with the estimating values of the unknown features of the series of objects, inserting the training object within the series of objects, and
- updating a model of the array of models corresponding to the Y-variable value of the training object, based at least in part on the X-variable values of the training object and of existing X-variable values of the model.
Dependencies are inferred from the claim text.