Table 15.
Comparing F1-score of deep learning models (Thai sentences dataset) with focusing POS tags (N+Adj+Det: NAD).
Input | Model | Micro-averaged |
Macro-averaged |
||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
P | R | (Mean) | (SD) | (Max) | P | R | (Mean) | (SD) | (Max) | ||
Original | CNN | 0.7793 | 0.7793 | 0.7793 | 0.0119 | 0.7989 | 0.7790 | 0.7759 | 0.7756 | 0.0121 | 0.7962 |
BiLSTM | 0.7229 | 0.7229 | 0.7229 | 0.0245 | 0.7542 | 0.7323 | 0.7205 | 0.7183 | 0.0251 | 0.7517 | |
Hybrid | 0.7268 | 0.7268 | 0.7268 | 0.0210 | 0.7542 | 0.7397 | 0.7212 | 0.7231 | 0.0203 | 0.7512 | |
+all POS Tags | CNN | 0.7888 | 0.7888 | 0.7888 | 0.0195 | 0.8156 | 0.7917 | 0.7865 | 0.7862 | 0.0203 | 0.8142 |
BiLSTM | 0.7523 | 0.7523 | 0.7523 | 0.0357 | 0.7598 | 0.7583 | 0.7475 | 0.7476 | 0.0339 | 0.7592 | |
Hybrid | 0.7467 | 0.7467 | 0.7467 | 0.0312 | 0.7542 | 0.7520 | 0.7528 | 0.7463 | 0.0300 | 0.7522 | |
+focusing Tags | CNN | 0.7955 | 0.7955 | 0.7955 | 0.0188 | 0.8324 | 0.7976 | 0.7929 | 0.7932 | 0.0189 | 0.8309 |
BiLSTM | 0.7162 | 0.7162 | 0.7162 | 0.0111 | 0.7263 | 0.7212 | 0.7133 | 0.7120 | 0.0119 | 0.7317 | |
Hybrid | 0.7503 | 0.7503 | 0.7503 | 0.0227 | 0.7877 | 0.7540 | 0.7467 | 0.7441 | 0.0208 | 0.7758 | |
+focusing Words | CNN | 0.7313 | 0.7313 | 0.7313 | 0.0107 | 0.7347 | 0.7266 | 0.7271 | 0.7542 | 0.0102 | 0.7471 |
BiLSTM | 0.6777 | 0.6777 | 0.6777 | 0.0318 | 0.7207 | 0.6834 | 0.6748 | 0.6740 | 0.0320 | 0.7161 | |
Hybrid | 0.7000 | 0.7000 | 0.7000 | 0.0225 | 0.7207 | 0.7267 | 0.7155 | 0.7191 | 0.0225 | 0.7191 |