Table 1 Comparison before different classifiers
From: Research on image classification model based on deep convolution neural network
Categorizer | Accuracy on training set | Accuracy on the test set | Time-consuming(s) |
|---|---|---|---|
CNN | 99.68% | 83.67% | 6.003 |
SVM-RBF | 89.41% | 87.63% | 9.334 |
NB | 90.78% | 89.36% | 7.392 |
KNN | 81.25% | 72.59% | 7.348 |
RF | 85.26% | 79.31% | 1.203 |
DT | 100% | 69.47% | 3.137 |
GBDT | 87.79% | 76.23% | 6.947 |