Active Learning for Chinese Word Segmentation in Medical Text
TABLE V: Comparison with Different Clustering Features.
['Model + feasure', 'Precision', 'Recall', 'F_{1}-score']
, we also compare K-means with 3 different clustering features, including MeanShift [comaniciu2002mean], SpectralClustering [ng2002spectral] and DBSCAN [ester1996density] on training and testing sets. Among these clustering features, K-means performs best, so we utlize K-means results as additional features for CRF-based segmenter.