8. A non-transitory computer-readable storage that stores instructions which, when executed by one or more processors, cause the one of more processors to perform the steps of: training a source language text classifier based on labeled training data that is composed in the source language, thereby producing a source language model; translating source language features from the source language model into a target language, thereby producing a target language model; and applying a target language classifier, which uses the target language model, to a particular document that is composed in the target language, thereby determining whether the particular document belongs to a particular class; wherein the source language classifier determines, based on said training, whether documents composed in the source language belong to the particular class; wherein translating the source language features comprises automatically selecting, for a particular source language feature of the source language features, a particular target language translation of a plurality of possible target language translations of the particular source language feature; and wherein selecting the particular target language translation is based at least in part on an expectation maximum; wherein selecting the particular target language translation based at least in part on the expectation maximum comprises: determining a first probability based at least in part on the particular target language translation during a first iteration; determining a second probability based at least in part on the particular target language translation during a second iteration; determining whether a difference between the first probability and the second probability is less than a specified threshold; in response to determining that the difference between the first probability and the second probability is less than the specified threshold, setting a final translation probability for the particular target language translation equal to the second probability; and selecting the particular target language translation based at least in part on the final translation probability.
8. A non-transitory computer-readable storage that stores instructions which, when executed by one or more processors, cause the one of more processors to perform the steps of: training a source language text classifier based on labeled training data that is composed in the source language, thereby producing a source language model; translating source language features from the source language model into a target language, thereby producing a target language model; and applying a target language classifier, which uses the target language model, to a particular document that is composed in the target language, thereby determining whether the particular document belongs to a particular class; wherein the source language classifier determines, based on said training, whether documents composed in the source language belong to the particular class; wherein translating the source language features comprises automatically selecting, for a particular source language feature of the source language features, a particular target language translation of a plurality of possible target language translations of the particular source language feature; and wherein selecting the particular target language translation is based at least in part on an expectation maximum; wherein selecting the particular target language translation based at least in part on the expectation maximum comprises: determining a first probability based at least in part on the particular target language translation during a first iteration; determining a second probability based at least in part on the particular target language translation during a second iteration; determining whether a difference between the first probability and the second probability is less than a specified threshold; in response to determining that the difference between the first probability and the second probability is less than the specified threshold, setting a final translation probability for the particular target language translation equal to the second probability; and selecting the particular target language translation based at least in part on the final translation probability. 9. The non-transitory computer-readable storage of claim 8 , wherein the steps further comprise: applying the target language classifier to a set of unlabelled documents that are composed in the target language, thereby producing a set of automatically labeled target language documents; training a new target language text classifier based on the set of automatically labeled target language documents, thereby producing a tuned target language model; and applying a new target language classifier, which uses the tuned target language model, to the particular document that is composed in the target language, thereby determining whether the particular document belongs to the particular class.