Table 6:
Method | Prec. | Rec. | F1 | Acc |
---|---|---|---|---|
Stochastic gradient descent (l1 = 0.95, loss = hinge) | 0.90 | 0.88 | 0.89 | 0.93 |
Multinomial naive Bayes (alpha = 1) | 0.95 | 0.81 | 0.87 | 0.92 |
Perceptron | 0.83 | 0.87 | 0.85 | 0.89 |
Passive aggressive (loss = sqrt_hinge) | 0.90 | 0.89 | 0.9 | 0.93 |
RSDD trained model | 0.95 | 0.43 | 0.6 | 0.8 |