SYSTEMS FOR SECOND-ORDER PREDICTIVE DATA ANALYTICS, AND RELATED METHODS AND APPARATUS
First Claim
1. A predictive modeling method comprising:
- obtaining a fitted, first-order predictive model, wherein the first-order predictive model is configured to predict values of one or more output variables of a prediction problem based on values of one or more first input variables; and
performing a second-order predictive modeling procedure on the fitted, first-order model, wherein the second-order modeling procedure is associated with a second-order predictive model, and wherein performing the second-order predictive modeling procedure on the fitted, first-order model includes;
generating second-order input data including a plurality of second-order observations, wherein each second-order observation includes respective observed values of one or more second input variables and predicted values of the output variables, and wherein generating the second-order input data comprises, for each second-order observation;
obtaining the respective observed values of the second input variables and corresponding observed values of the first input variables, and applying the first-order predictive model to the corresponding observed values of the first input variables to generate the respective predicted values of the output variables,generating, from the second-order input data, second-order training data and second-order testing data,generating a fitted second-order predictive model of the fitted first-order model by fitting the second-order predictive model to the second-order training data, andtesting the fitted, second-order predictive model of the fitted first-order model on the second-order testing data.
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Abstract
A predictive modeling method may include obtaining a fitted, first-order predictive model configured to predict values of output variables based on values of first input variables; and performing a second-order modeling procedure on the fitted, first-order model, which may include: generating input data including observations including observed values of second input variables and predicted values of the output variables; generating training data and testing data from the input data; generating a fitted second-order model of the fitted first-order model by fitting a second-order model to the training data; and testing the fitted, second-order model of the first-order model on the testing data. Each observation of the input data may be generated by (1) obtaining observed values of the second input variables, and (2) applying the first-order predictive model to corresponding observed values of the first input variables to generate the predicted values of the output variables.
127 Citations
30 Claims
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1. A predictive modeling method comprising:
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obtaining a fitted, first-order predictive model, wherein the first-order predictive model is configured to predict values of one or more output variables of a prediction problem based on values of one or more first input variables; and performing a second-order predictive modeling procedure on the fitted, first-order model, wherein the second-order modeling procedure is associated with a second-order predictive model, and wherein performing the second-order predictive modeling procedure on the fitted, first-order model includes; generating second-order input data including a plurality of second-order observations, wherein each second-order observation includes respective observed values of one or more second input variables and predicted values of the output variables, and wherein generating the second-order input data comprises, for each second-order observation;
obtaining the respective observed values of the second input variables and corresponding observed values of the first input variables, and applying the first-order predictive model to the corresponding observed values of the first input variables to generate the respective predicted values of the output variables,generating, from the second-order input data, second-order training data and second-order testing data, generating a fitted second-order predictive model of the fitted first-order model by fitting the second-order predictive model to the second-order training data, and testing the fitted, second-order predictive model of the fitted first-order model on the second-order testing data. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29)
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30. A predictive modeling apparatus comprising:
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a memory configured to store a machine-executable module encoding a second-order predictive modeling procedure associated with a second-order predictive model, wherein the second-order predictive modeling procedure includes a plurality of tasks including at least one pre-processing task and at least one model-fitting task; and at least one processor configured to execute the machine-executable module, wherein executing the machine-executable module causes the apparatus to perform the second-order predictive modeling procedure on a fitted, first-order predictive model, including; performing the pre-processing task, including obtaining the fitted, first-order predictive model, wherein the first-order predictive model is configured to predict values of one or more output variables of a prediction problem based on values of one or more first input variables; and performing the model-fitting task, including; generating second-order input data including a plurality of second-order observations, wherein each second-order observation includes respective observed values of one or more second input variables and predicted values of the output variables, and wherein generating the second-order input data comprises, for each second-order observation;
obtaining the respective observed values of the second input variables and corresponding observed values of the first input variables, and applying the first-order predictive model to the corresponding observed values of the first input variables to generate the respective predicted values of the output variables,generating, from the second-order input data, second-order training data and second-order testing data, generating a fitted second-order predictive model of the fitted first-order model by fitting the second-order predictive model to the second-order training data, and testing the fitted, second-order predictive model of the fitted first-order model on the second-order testing data.
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Specification