| 摘要 |
Statistical machine learning, in which an input module receives user input that defines a hypothesis associated with a particular Output. The hypothesis defines one or more starting criteria that are proposed as being correlated with the particular output, and a recommendation engine initially provides recommendations that include the particular output based on the one or more starting criteria defined by the hypothesis. An experience analytics system receives feedback data related to whether the recommendations provided based on the one or more starting criteria defined by the hypothesis were successful and modifies the hypothesis based on the feedback data. Subsequent to the experience analytics system modifying the hypothesis, the recommendation engine provides recommendations that include the particular output based on the modified hypothesis.
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