13. The system of claim 12 , wherein classifying an item as positive is based at least in part on a score associated with the item being sufficiently high.
12. A system for use in an online advertising exchange, comprising one or more server computers coupled to the Internet; and one or more databases coupled to the one or more server computers; wherein the one or more server computers are for: constructing a machine learning-based and pairwise ranking method-based classification model for binary classification of items as positive or negative with regard to a single class based on training using a training set of examples comprising positive examples and unlabelled examples with regard to the class; wherein the model comprises a plurality of features, a single hyperparameter, a single threshold parameter, and a decision function; and wherein the training of the model comprises learning a plurality of weighting parameters, each of the plurality of weighting parameters mapping to a feature of the plurality of features, in such a way that positive examples are to be scored higher, in connection with being positive, than unlabelled examples; and wherein the hyperparameter and the threshold parameter are selected for optimal model performance with regard to, in connection with the single class, constraining positive items to be classified as positive while minimizing a number of unlabelled items to be classified as positive; storing the model, comprising the features, the mapping of the weighting parameters with the features, the weighting parameters, the hyperparameter, the threshold parameter, and the decision function, in at least one of the one or more databases; and using the decision function for classifying items as positive or negative with regard to the class, wherein the deciding is based at least in part on scores and the threshold parameter.