Goal seeking using predictive analytics
First Claim
Patent Images
1. A system that facilitates goal seeking in tabular data, comprising:
- a processor;
system memory;
a receiver component that receives a desired goal based on tabular data, the goal comprising a substantially increased likelihood that the tabular data of a target column has a target value, wherein the receiver component is configured to receive and process both categorical goals comprising at least a target column that contains a finite set of categorical values and continuous goals comprising the target column that contains values in a range or interval;
an optimization component that optimizes goal seeking for at least one degree of freedom, wherein optimizing includes determining patterns for a selected row that determine a value of a target column as a function of the other columns within the tabular data, the determined patterns providing at least one row value that increases the likelihood of reaching the desired goal in the target column, the row values being inferred using probabilistic inference, wherein the probabilistic inference includes computing a probability distribution over states of interest based on a consideration of data and events of rows other than the selected row, wherein the row values are based on the probability they yield for the goal value if categorical goals were received and are based on the closest estimation to the goal if continuous goals were received; and
an output component that presents recommended actions within the tabular data to achieve the desired goal.
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Abstract
Seeking goals in data that can be expressed as rows and columns is provided through predictive analytics. If a desired goal is achievable, the changes to the rows and/or columns that can achieve the goal are presented to a user. If the desired goal is not achievable, an error message or other indicator can be presented to the user. Predictive analytics can include a predictive algorithm, various data mining techniques, or other predictive techniques. A confidence metric of a goal-seek result can be normalized to estimate the degree of confidence that a particular change will yield the desired outcome.
34 Citations
20 Claims
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1. A system that facilitates goal seeking in tabular data, comprising:
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a processor; system memory; a receiver component that receives a desired goal based on tabular data, the goal comprising a substantially increased likelihood that the tabular data of a target column has a target value, wherein the receiver component is configured to receive and process both categorical goals comprising at least a target column that contains a finite set of categorical values and continuous goals comprising the target column that contains values in a range or interval; an optimization component that optimizes goal seeking for at least one degree of freedom, wherein optimizing includes determining patterns for a selected row that determine a value of a target column as a function of the other columns within the tabular data, the determined patterns providing at least one row value that increases the likelihood of reaching the desired goal in the target column, the row values being inferred using probabilistic inference, wherein the probabilistic inference includes computing a probability distribution over states of interest based on a consideration of data and events of rows other than the selected row, wherein the row values are based on the probability they yield for the goal value if categorical goals were received and are based on the closest estimation to the goal if continuous goals were received; and an output component that presents recommended actions within the tabular data to achieve the desired goal. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A computer-implemented dynamic goal method for dynamic goal seeking in tabular data, comprising:
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receiving an input that includes a desired goal expressed within tabular data, the goal comprising a substantially increased likelihood that the tabular data of a target column has a target value, wherein receiving includes receiving and processing both categorical goals comprising at least a target column that contains a finite set of categorical values and continuous goals comprising the target column that contains values in a range or interval; uploading the tabular data as at least one rowset parameter; and building a predictive model based in part on the at least one rowset parameter and the desired goal, wherein the desired goal is optimized, the optimizing includes determining patterns for a selected row that determine a value of a target column as a function of the other columns within the tabular data, the determined patterns providing a row value that increases the likelihood of reaching the desired goal in the target column, the row values being inferred using probabilistic inference, wherein the probabilistic inference includes computing a probability distribution over states of interest based on a consideration of data and events of rows other than the selected row, wherein the row values are based on the probability they yield for the goal value if categorical goals were received and are based on the closest estimation to the goal if continuous goals were received. - View Dependent Claims (13, 14, 15, 16, 17)
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18. A computer executable system including a processor and system memory that provides recommends actions to achieve a goal relating to tabular data, comprising:
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means for receiving a desired goal represented by a plurality of columns and a plurality of rows, the goal comprising a substantially increased likelihood that the tabular data of a target column has a target value, wherein receiving includes receiving and processing both categorical goals comprising at least a target column that contains a finite set of categorical values and continuous goals comprising the target column that contains values in a range or interval; means for evaluating the plurality of columns and the plurality of rows, the evaluating including optimizing the desired goal, wherein the optimizing includes determining patterns for a selected row that determine a value of a target column as a function of the other columns within the tabular data, the determined patterns providing a row value that increases the likelihood of reaching the desired goal in the target column, the row values being inferred using probabilistic inference, wherein the probabilistic inference includes computing a probability distribution over states of interest based on a consideration of data and events of rows other than the selected row, wherein the row values are based on the probability they yield for the goal if continuous goals were received; means for determining a change to at least one of the plurality of columns or at least one of the plurality of row to achieved the desired result or both; and means for presenting the results of the determination. - View Dependent Claims (19, 20)
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Specification