PARTITIONING DATA FOR TRAINING MACHINE-LEARNING CLASSIFIERS

摘要

Various embodiments relating to partitioning a data set for training machine-learning classifiers based on an output of a globally trained machine-learning classifier are disclosed. In one embodiment, a first machine-learning classifier may be trained on a set of training data to produce a corresponding set of output data. The set of training data may be partitioned into a plurality of subsets based on the set of output data. Each subset may correspond to a different class. A second machine-learning classifier may be trained on the set of training data using a plurality of classes corresponding to the plurality of subsets to produce, for each data object of the set of training data, a probability distribution having for each class a probability that the data object is a member of the class.