Detecting Dementia in Mandarin Chinese using Transfer Learning from a Parallel Corpus
Table 2: Top English features for joint feature selection.
['#', '[BOLD] Feature Name', '[ITALIC] R2']
With K<13, performance suffers because the DementiaBank classifier is not given enough information to make accurate classifications. With K>13, the accuracy for the DementiaBank classifier improves; however, the overall performance degrades because it is given noisy features with low R2 coefficients. The top performing model uses the first 13 features.