Medical abstracts describe the current conditions of a patient. Doctors routinely scan dozens or hundreds of abstracts each day as they do their rounds in a hospital and must quickly pick up on the salient information pointing to the patient’s malady. You are trying to design assistive technology that can identify, with high precision, the class of problems described in the abstract. In the given dataset, abstracts from 5 different conditions have been included: digestive system diseases, cardiovascular diseases, neoplasms, nervous system diseases, and general pathological conditions.

The training dataset consists of 14438 records and the test dataset consists of 14442 records. The train data has classes whereas, the test data classes are needed to be predicted.

The data are provided as text in train.dat and test.dat, which should be processed appropriately.