Legal Question Answering using Ranking SVM and Deep Convolutional Neural Network
Table 4: F1-score when excluding some features from all feature set
['[BOLD] Feature All', '[BOLD] F1-score 0.5543', '[BOLD] Feature Groups All', '[BOLD] F1-score 0.5543']
: The contribution of each feature was investigated by using leave-one-out test. However when excluding Jaccard, F1-score drops to around 0.5. In contrast, when other features are excluded individually from the feature set, the result remains stable or goes up slightly. From this result, we conclude that Jaccard feature significantly contributes to SVM-Rank performance.