Research Paper
Table 1. Dataset Specifications
['Dataset', 'Train Size', 'Test Size', '# Classes']
For our experiments, we have chosen three popular publicly-available news classification datasets. The dataset is partitioned almost evenly across 20 different classes: comp.graphics, comp.os.ms-windows.misc, comp.sys.ibm.pc.hardware, comp.sys.mac. hardware, comp. windows.x, rec.autos, rec.motorcycles, rec.sport. baseball, rec.sport. hockey, sci.crypt, sci.electronics, sci.med, sci.space, misc.forsale, talk.politics.misc, talk.politics.guns, talk. politics.mideast, talk. religion.misc, alt.atheism and soc. religion.christian. The dataset is divided into 5 major classes: athletics, cricket, football, rugby and tennis. The datasets are chosen in such a way that all of them share common domain knowledge and have small number of training examples so that the improvement observed using instance-infusion is significant.