Segmented predictive model system
First Claim
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1. A predictive model method, comprising:
- using a computer to perform at least one of the steps of;
receiving first input data into a plurality of different types of initial predictive models to develop an initial model configuration by selecting an input data set from the plurality of predictive models using a variable selection algorithm after a training of each predictive model type is completed;
receiving the input data set from said initial model configuration as an inputs into a second, model stage to develop an improvement to said initial model configuration and input data set as an output; and
receiving said second model stage output as an input into a third predictive model stage to develop and output a final predictive model where all the input data represents a physical object or substance and where the final predictive model consists of a linear predictive model or a nonlinear predictive model.
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Abstract
A computer program product, method and system for transforming data into predictive models. The transformation of data into predictive models comprises a multi stage learning process that uses a plurality of algorithms at each stage to select output for use in the next stage. The final predictive model is a linear or nonlinear predictive model. Analyses of the model and the variables associated with it can be used to produce graphs and other management reports.
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Citations
25 Claims
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1. A predictive model method, comprising:
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using a computer to perform at least one of the steps of; receiving first input data into a plurality of different types of initial predictive models to develop an initial model configuration by selecting an input data set from the plurality of predictive models using a variable selection algorithm after a training of each predictive model type is completed; receiving the input data set from said initial model configuration as an inputs into a second, model stage to develop an improvement to said initial model configuration and input data set as an output; and receiving said second model stage output as an input into a third predictive model stage to develop and output a final predictive model where all the input data represents a physical object or substance and where the final predictive model consists of a linear predictive model or a nonlinear predictive model. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A computerized apparatus, comprising:
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means for receiving first input data into a plurality of different types of initial computerized predictive models to develop an initial model configuration by selecting an input data set from the plurality of predictive models using a variable selection algorithm after a training of each predictive model type is completed; means for receiving the input data set from said initial model configuration and a second input data as inputs into a second, model stage to develop an improvement to said initial model configuration as an output, said second input data comprising one of said first input data, data not included in said first input data, and a combination thereof; and means for receiving said second model stage output as an input into a third predictive model stage to develop and output a final predictive model where the final predictive model consists of a linear predictive model or a nonlinear predictive model. - View Dependent Claims (9, 10, 11, 12, 13)
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14. A machine-readable medium tangibly embodying a program of non-transitory, machine-readable instructions executable by a digital processing apparatus to complete data transformation steps, comprising:
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receiving first input data into a plurality of different types of initial predictive models to develop an initial model configuration by selecting an input data set from the plurality of predictive models using a variable selection algorithm after a training of each predictive model type is completed; receiving the input data set from said initial model configuration and a second input data as inputs into a second, model stage to develop an improvement to said initial model configuration as an output, said second input data comprising one of said first input data, data not included in said first input data, and a combination thereof; and receiving said second model stage output as an input into a third predictive model stage to develop and output a final predictive model where the final predictive model consists of a linear predictive model or a nonlinear predictive model. - View Dependent Claims (15, 16, 17, 18, 19, 20)
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21. A non-transitory computer program product tangibly embodied on a computer readable medium and comprising a program code for directing at least one computer to:
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receive first input data into a plurality of different types of initial predictive models to develop an initial model configuration by selecting an input data set from the plurality of predictive models using a variable selection algorithm after a training of each predictive model type is completed; receive the input data set from said initial model configuration as an input into a second, model stage to develop an improvement to said initial model configuration and input data set as an output; and receive said second model stage output as an input into a third predictive model stage to develop and output a final predictive model where the final predictive model consists of a linear predictive model or a nonlinear predictive model. - View Dependent Claims (22, 23, 24, 25)
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Specification