SentiCite \subtitleAn Approach for Publication Sentiment Analysis
Table 9: Ten run k-fold cross-fold for SentiCite (SC).
['[BOLD] Algorithm', '[BOLD] F1', '[BOLD] F2', '[BOLD] F3', '[BOLD] F4', '[BOLD] F5', '[BOLD] F6', '[BOLD] F7', '[BOLD] F8', '[BOLD] F9', '[BOLD] F10', '[BOLD] Overall']
Finally, to validate that the results of the approach are correct a cross validation was done. The cross validation was done with the training corpus to have a balanced number of all classes. Therefore, the classifier was trained with a subset of the training corpus and evaluated on the remaining documents. This procedure as repeated 10 times with different splits. Also, this was the reason why the performance decreased because there was less training data. This was done because the training corpus was very large and the test corpus has for some labels only a few examples which was the case because of the distribution of the documents. The cross-validation was done exclusively with the training set which was split into two sets one for training and one for testing.