Patent Document ID: 8744987
Application ID: 11406689

Base Claim:
1. At least one computer program provided on at least one non-transitory computer readable storage medium and comprising code that when executed causes at least one computer to perform a method comprising: training a machine learning classifier with a set of labeled training data, such that the trained classifier is operable to determine a score with respect to the classification of cases for a category; determining at least one first distribution of scores for positive cases in the training set, wherein a positive case is a case that belongs to the category; determining at least one second distribution of scores for negative cases in the training set, wherein a negative case is a case that does not belong to the category; determining a third distribution of scores generated by the classifier classifying cases in a set of target data; and estimating a proportion of cases in the target set that are positive cases by fitting the at least one first distribution and the at least one second distribution to the third distribution.

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Claim 2:
2. The at least one computer program of claim 1 , wherein estimating a proportion of cases in the target set that are positive cases by fitting the at least one first distribution and the at least one second distribution to the third distribution further comprises: determining a plurality of mixtures, each of the plurality of mixtures including a combination of the at least one first and the at least one second distributions; evaluating how well each of the plurality of mixtures fits the third distribution; selecting a mixture from the plurality of mixtures based on the evaluating; and determining the proportion of the cases that are positive based on the selected mixture.