1. A computer-implemented method comprising: selecting a collection of documents to classify; selecting a plurality of classifiers for scoring a document with respect to a specified property; for each document in the collection, applying each of the plurality of classifiers, each classifier generating a score associated with a likelihood that the document has the specified property, combining the scores from each classifier including applying a multiple classifier model, and classifying the document as having the specified property based on the combined score; where the multiple classifier model is generated by: identifying a training group of documents; calculating classifier scores for each document in the training group of documents using the plurality of classifiers; determining whether each document in the training group of documents has the specified property; and generating a maximum likelihood estimate for a probability distribution by applying monotonic regression to classifier scores of each document in the training group of documents, where each classifier generates classifier scores of a document that monotonically increase with an increase in the likelihood that the document has the specified property.