Text Classification with Tournament Methods

This paper compares the effectiveness of n-way (n > 2) classification using a probabilistic classifier to the use of multiple binary probabilistic classifiers. We describe the use of binary classifiers in both Round Robin and Elimination tournaments, and compare both tournament methods and n-way classification when determining the language of origin of speakers (both native and non-native English speakers) speaking English. We conducted hundreds of experiments by varying the number of categories as well as the categories themselves. In all experiments the tournament methods performed better than the n-way classifier, and of these tournament methods, on average, Round Robin performs slightly better than the Elimination tournament.