Patent Document ID: 8923608
Application ID: 13783581

Base Claim:
1. A computer-implemented method for evaluating training data comprising: receiving training data comprising a labeled training set of digital objects, at least some of the digital objects in the labeled training set including a label indicating that the digital object is positive for a respective class selected from a predetermined set of classes with which a classifier is to be trained; grouping the positively labeled digital objects in the labeled training set into positive label groups, one positive label group for each class in the set of classes, each label group comprising digital objects having a label indicating the digital object is positive for the respective class; with a trained categorizer, assigning a score vector to each digital object in the labeled training set of digital objects, the score vector comprising a score for each category of a predetermined set of categories; applying at least one heuristic to the training data to evaluate the training data for training the classifier based on the assigned score vectors and training data labels; and based on the at least one heuristic, providing an evaluation of the training data prior to training the classifier.

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Claim 23:
23. The method of claim 1 , wherein the received training data comprises a set of unlabeled digital objects, the method further comprising: with the categorizer, assigning a score vector to each digital object in the set of unlabeled digital objects, the score vector comprising a score for each category of the set of categories; and wherein the applying of the at least one heuristic comprises applying a heuristic configured for identifying at least one class which is not represented in the set of unlabeled digital objects.