Updateable predictive analytical modeling
First Claim
1. A computer-implemented system comprising:
- one or more computers;
one or more data storage devices coupled to the one or more computers, storing;
a repository of training functions,a predictive model repository of trained predictive models, including a plurality of updateable trained predictive models, and wherein each trained predictive model is associated with an effectiveness score that represents an estimation of the effectiveness of the respective trained predictive model, andinstructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising;
receiving over a network a series of training data sets for predictive modeling from a client computing system, wherein training data included in the training data sets is different from initial training data that was used with a plurality of training functions obtained from the repository to train the trained predictive models stored in the predictive model repository;
using the series of training data sets, a plurality of trained updateable predictive models obtained from the predictive model repository and a plurality of training functions obtained from the repository of training functions to generate a plurality of retrained predictive models;
generating an effectiveness score for each of the plurality of retrained predictive models;
selecting a first trained predictive model from among the plurality of trained predictive models included in the predictive model repository and the plurality of retrained predictive models based on their respective effectiveness scores; and
providing access to the first trained predictive model over the network.
2 Assignments
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Accused Products
Abstract
Methods, systems, and apparatus, including computer programs encoded on one or more computer storage devices, for training and retraining predictive models. A series of training data sets for predictive modeling can be received, e.g., over a network from a client computing system. The training data included in the training data sets is different from initial training data that was used with multiple training functions to train multiple trained predictive models stored in a predictive model repository. The series of training data sets are used with multiple trained updateable predictive models obtained from the predictive model repository and multiple training functions to generate multiple retrained predictive models. An effectiveness score is generated for each of the retrained predictive models. A first trained predictive model is selected from among the trained predictive models included in the predictive model repository and the retrained predictive models based on their respective effectiveness scores.
110 Citations
25 Claims
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1. A computer-implemented system comprising:
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one or more computers; one or more data storage devices coupled to the one or more computers, storing; a repository of training functions, a predictive model repository of trained predictive models, including a plurality of updateable trained predictive models, and wherein each trained predictive model is associated with an effectiveness score that represents an estimation of the effectiveness of the respective trained predictive model, and instructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising; receiving over a network a series of training data sets for predictive modeling from a client computing system, wherein training data included in the training data sets is different from initial training data that was used with a plurality of training functions obtained from the repository to train the trained predictive models stored in the predictive model repository; using the series of training data sets, a plurality of trained updateable predictive models obtained from the predictive model repository and a plurality of training functions obtained from the repository of training functions to generate a plurality of retrained predictive models; generating an effectiveness score for each of the plurality of retrained predictive models; selecting a first trained predictive model from among the plurality of trained predictive models included in the predictive model repository and the plurality of retrained predictive models based on their respective effectiveness scores; and providing access to the first trained predictive model over the network. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15)
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16. A computer-implemented method comprising:
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receiving over a network a series of training data sets for predictive modeling from a client computing system, wherein training data included in the training data sets is different from initial training data that was used with a plurality of training functions obtained from a repository of training functions to train a plurality of trained predictive models stored in a predictive model repository; using the series of training data sets, a plurality of trained updateable predictive models obtained from the predictive model repository and a plurality of training functions obtained from the repository of training functions to generate a plurality of retrained predictive models; generating an effectiveness score for each of the plurality of retrained predictive models; selecting a first trained predictive model from among the plurality of trained predictive models included in the predictive model repository and the plurality of retrained predictive models based on their respective effectiveness scores; and providing access to the first trained predictive model over the network. - View Dependent Claims (17, 18, 19, 20)
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21. A computer-readable storage device encoded with a computer program product, the computer program product comprising instructions that when executed on one or more computers cause the one or more computers to perform operations implementing an adaptable predictive model training system, the operations comprising:
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receiving over a network a series of training data sets for predictive modeling from a client computing system, wherein training data included in the training data sets is different from initial training data that was used with a plurality of training functions obtained from a repository of training functions to train a plurality of trained predictive models stored in a predictive model repository; using the series of training data sets, a plurality of trained updateable predictive models obtained from the predictive model repository and a plurality of training functions obtained from the repository of training functions to generate a plurality of retrained predictive models; generating an effectiveness score for each of the plurality of retrained predictive models; selecting a first trained predictive model from among the plurality of trained predictive models included in the predictive model repository and the plurality of retrained predictive models based on their respective effectiveness scores; and providing access to the first trained predictive model over the network. - View Dependent Claims (22, 23, 24, 25)
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Specification