Gap-weighted subsequences for automatic cognate identification and phylogenetic inference
Table 5: Performance of subsequence features on subfamily test set.
['Features', 'ACC', 'MCC', 'AP']
The first set of experiments consist of testing the performance of subsequence based features against HK features on multiple aspects. The results suggest that the subsequence features perform consistently over p∈[2,7]. The p=3 based linear classifier performs the best across all the evaluation measures. All the subsequence based features agree on AP score and perform better than HK classifier. The subsequence-based features outperform at MCC and ACC evaluation measures.