| 摘要 |
Disclosed are methods and apparatus for optimizing results produced by a predictive model in order to determine which action to perform out of a plurality of actions. In an operation (a), a plurality of goal metrics are provided for a plurality of possible actions based on a plurality of input conditions. One or more of the goal metrics are produced by one or more predictive models. In an operation (b), the plurality of goal metrics are normalized. In an operation (c), for each possible action a total of each of the normalized goal metrics multiplied by a corresponding predetermined weight is determined. In an operation (d), the totals determined for the plurality of possible actions are compared to thereby determine a highest total. In an operation (e), an action selected from the plurality of possible actions is performed, where the selected action has the highest total. In one implementation, operations (a) through (e) are repeated for a plurality of sets of input conditions, and normalizing the goal metrics for a current set of input conditions is accomplished by assigning a point value for each goal metric of each action, wherein the point value corresponds to the percentage of previously determined corresponding goal metric values that are less valuable than the current goal metric value
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