Linear Ensembles of Word Embedding Models
Table 3: Hit@1 and Hit@10 accuracies of the analogy test. SOLS and SOPP columns show the accuracies of the combined models. Mean W, Min W and Max W show the mean, minimum and maximum accuracies of the initial models Wi, respectively. The best accuracy among the combined models and the mean of the initial models is given in bold. The last row shows the average accuracies over all embedding sizes.
['[BOLD] Dim', '[BOLD] Hit@1  [BOLD] SOLS', '[BOLD] Hit@1  [BOLD] SOPP', '[BOLD] Hit@1  [BOLD] Mean  [ITALIC] W', '[BOLD] Hit@1  [BOLD] Min  [ITALIC] W', '[BOLD] Hit@1  [BOLD] Max  [ITALIC] W', '[BOLD] Hit@10  [BOLD] SOLS', '[BOLD] Hit@10  [BOLD] SOPP', '[BOLD] Hit@10  [BOLD] Mean  [ITALIC] W', '[BOLD] Hit@10  [BOLD] Min  [ITALIC] W', '[BOLD] Hit@10  [BOLD] Max  [ITALIC] W']
The SOPP combined model is better than the mean of the initial models in all six cases. Furthermore, it is consistently above the maximum of the best initial models. The average accuracy of SOPP is better than the average of the mean accuracies of initial models by 41%, relatively (7.7% in absolute) in terms of Hit@1 and 27% relatively (10.5% in absolute) in terms of Hit@10.