Table 4.
Comparison of selected machine learning models for different Q.
Model | Q | |||||
---|---|---|---|---|---|---|
10 | 25 | 50 | 100 | 150 | 200 | |
DT | 61.84 | 62.42 | 66.25 | 71.32 | 77.6 | 74.36 |
KNN | 77.34 | 77.51 | 78.84 | 81.73 | 82.4 | 76.92 |
RF | 66.2 | 69.75 | 72.93 | 82.23 | 84.8 | 76.92 |
NN | 58.31 | 59.72 | 63.54 | 69.04 | 76.0 | 71.79 |
LSTM | 57.76 | 55.54 | 54.14 | 54.06 | 60.8 | 64.1 |
CNN | 46.94 | 49.16 | 48.16 | 53.05 | 51.2 | 56.41 |
Transformer | 50.86 | 54.84 | 60.06 | 54.06 | 24.8 | 35.9 |
Dataset size | (49,597, 10, 3) | (14,249, 30, 3) | (7184, 50, 3) | (1966, 100, 3) | (624, 150, 3) | (195, 200, 3) |