Methods and apparatus for predictive analysis
First Claim
1. A non-transitory computer-readable medium containing instructions for causing a computer system to process data according to a predictive modeling system, the predictive modeling system comprising:
- a plurality of artificial agents responsive to an input data set, wherein;
at least one artificial agent comprises a predictive algorithm;
the input data set comprises at least one intake data set and at least one outcome data set, wherein;
a first intake data set corresponds to a set of factors for a first cohort at an initial state in time; and
a first outcome data set corresponds to a change in the set of factors for the first cohort after a passage of time;
each artificial agent produces a correlation data set relating at least a portion of the first outcome data set with at least a portion of the first intake data set for predicting a future change to a second cohort over a second passage of time based on a second intake data set corresponding to a second set of factors for the second cohort at a second initial state in time; and
each artificial agent produces a predictability value for quantifying an accuracy of the correlation data set produced by the artificial agent; and
an agent factory responsive to the input data set, wherein the agent factory produces the plurality of artificial agents in response to the input data set.
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Abstract
Methods and apparatus for predictive analytics generally comprise one or more artificial agents and an agent factory. An artificial agent may be responsive to at least one of an internal data set and an external data set. Further, an artificial agent may produce a correlation data set relating an outcome data set and at least one of the internal data set and the external data set. In addition, an artificial agent may produce a predictability value corresponding to the correlation data set. The agent factory may be responsive to the outcome data set. Also, the agent factory may produce the artificial agent in response to the outcome data set.
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Citations
18 Claims
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1. A non-transitory computer-readable medium containing instructions for causing a computer system to process data according to a predictive modeling system, the predictive modeling system comprising:
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a plurality of artificial agents responsive to an input data set, wherein; at least one artificial agent comprises a predictive algorithm; the input data set comprises at least one intake data set and at least one outcome data set, wherein; a first intake data set corresponds to a set of factors for a first cohort at an initial state in time; and a first outcome data set corresponds to a change in the set of factors for the first cohort after a passage of time; each artificial agent produces a correlation data set relating at least a portion of the first outcome data set with at least a portion of the first intake data set for predicting a future change to a second cohort over a second passage of time based on a second intake data set corresponding to a second set of factors for the second cohort at a second initial state in time; and each artificial agent produces a predictability value for quantifying an accuracy of the correlation data set produced by the artificial agent; and an agent factory responsive to the input data set, wherein the agent factory produces the plurality of artificial agents in response to the input data set. - View Dependent Claims (2, 3, 4, 5, 6)
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7. A computer-implemented method for predictive modeling, comprising:
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receiving within an agent factory an input data set, wherein the input data set comprises at least one intake data set and at least one outcome data set, wherein; a first intake data set corresponds to a set of factors for a first cohort at an initial state in time; and a first outcome data set corresponds to a change in the set of factors for the first cohort after a passage of time; generating within the agent factory a plurality of artificial agents, wherein at least one artificial agent comprises a predictive algorithm; determining within each artificial agent a correlation data set relating at least a portion of the first outcome data set with at least a portion of the first intake data set for predicting a future change to a second cohort over a second passage of time based on a second intake data set corresponding to a second set of factors for the second cohort at a second initial state in time; and determining within each artificial agent a predictability value for quantifying an accuracy of the correlation data set produced by the artificial agent. - View Dependent Claims (8, 9, 10, 11, 12)
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13. A computer-implemented method for candidate screening, comprising:
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receiving within an agent factory an input data set, wherein the input data set comprises at least one of an intake data set and an outcome data set, wherein; a first intake data set corresponds to a set of factors for a first cohort at an initial state in time; and a first outcome data set corresponds to a change in the set of factors for the first cohort after a passage of time; generating within the agent factory a plurality of artificial agents, wherein at least one artificial agent comprises a predictive algorithm; determining within each artificial agent a correlation data set relating at least a portion of the first outcome data set with at least a portion of the first intake data set for predicting a future change to a second cohort over a second passage of time based on a second intake data set corresponding to a second set of factors for the second cohort at a second initial state in time; determining within each artificial agent a predictability value for quantifying an accuracy of the correlation data set produced by the artificial agent. - View Dependent Claims (14, 15, 16, 17, 18)
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Specification