1. A computer-implemented method, comprising: determining, by a data processing apparatus, a potential match candidate from among candidates ranked by predictors, each predictor respectively ranking the candidates according to likelihoods for matching an object as predicted by the respective predictor, and each predictor being different from each other predictor; identifying, for each predictor and by the data processing apparatus, a first value that specifies a likelihood of the potential match candidate for matching the object as predicted by the predictor; identifying, for each predictor and by the data processing apparatus, a second value that is proportional to the ranking of the potential match candidate as predicted by the predictor; determining, by the data processing apparatus, a class probability score for the potential match candidate using the first value for each predictor and the second value for each predictor, the class probability score representing a probability that the potential match candidate is a match to the object; determining, by the data processing apparatus, that the class probability score satisfies a threshold; and determining, by the data processing apparatus, that the potential match candidate matches the object in response to determining that the class probability score satisfies the threshold.
1. A computer-implemented method, comprising: determining, by a data processing apparatus, a potential match candidate from among candidates ranked by predictors, each predictor respectively ranking the candidates according to likelihoods for matching an object as predicted by the respective predictor, and each predictor being different from each other predictor; identifying, for each predictor and by the data processing apparatus, a first value that specifies a likelihood of the potential match candidate for matching the object as predicted by the predictor; identifying, for each predictor and by the data processing apparatus, a second value that is proportional to the ranking of the potential match candidate as predicted by the predictor; determining, by the data processing apparatus, a class probability score for the potential match candidate using the first value for each predictor and the second value for each predictor, the class probability score representing a probability that the potential match candidate is a match to the object; determining, by the data processing apparatus, that the class probability score satisfies a threshold; and determining, by the data processing apparatus, that the potential match candidate matches the object in response to determining that the class probability score satisfies the threshold. 4. The method of claim 1 , wherein identifying the first value for a predictor comprises: receiving object attribute values identifying attributes of the object; receiving candidate attribute values for each candidate, the candidate attribute values for each candidate identifying attributes of the candidate; generating a set of candidate/object feature value pairs, each candidate/object feature value pair including an object attribute value and a matching candidate attribute value; providing the set of candidate/object feature value pairs to the predictor; and receiving, from the predictor, the first value for the predictor.