Table 11 Training time of 16 combination of 4 embedding models and 4 classifiers (s)
From: Exploring best-matched embedding model and classifier for charging-pile fault diagnosis
Embedding models | RF | KNN | MLP | DT |
|---|---|---|---|---|
N-gram (n = 2) | 27.35 | 2.25 | 196.71 | 8.28 |
GloVe | 0.91 | 0.23 | 4.01 | 0.10 |
Word2Vec | 1.00 | 0.19 | 3.51 | 0.05 |
BERT | 1.11 | 0.23 | 3.87 | 0.09 |