Syntactic Recurrent Neural Network for Authorship Attribution
Table 2: The performance results of models on PAN 2012 dataset for authorship attribution task.
['[BOLD] Model', '[BOLD] Model', '[BOLD] Segment-Level Accuracy (%)  [BOLD] Validation', '[BOLD] Segment-Level Accuracy (%)  [BOLD] Test', '[BOLD] Document-Level Accuracy(%)']
We report both segment-level and document-level accuracy. As mentioned before, each document (novel) has been divided into the segments of 100 sentences. Therefore, each segment in a novel has classified independently and afterwards the label of each document is calculated as the majority voting of its constituent segments. According to the segment-level accuracy, the performance of all models has dropped significantly on the test set mainly because of insufficient training data. We expect that if the models are trained on enough writing samples per author, the test results would be closer to the validation results.