Analyzing the Language of Food on Social Media
TABLE V: Effects of varying the fraction of tweets used for training and testing on classification accuracy in the city-prediction task, using All Words and LDA topics.
['training fraction', 'testing fraction 0.2', 'testing fraction 0.4', 'testing fraction 0.6', 'testing fraction 0.8', 'testing fraction 1.0']
Indeed, when only 20% of the training set is used, the models achieve the same score as the baseline classifier (6.67%). Performance continues to increase as we add more data, suggesting that we have not reached a performance ceiling yet.