Image Classification on Tree-MNIST 4 Classes (val)
86.51AccuracyCNN
Evaluation results
| Method | Links | ||||
|---|---|---|---|---|---|
| CNNArchitecture=2 Conv Layers2025.07 | 86.51 | 87.42 | 86.51 | 86.93 | |
| Random Forest2025.07 | 82.73 | 83.94 | 82.73 | 83.28 | |
| Gradient Boosting2025.07 | 81.95 | 82.87 | 81.95 | 82.35 | |
| K-Nearest Neighbors2025.07 | 79.84 | 81.03 | 79.84 | 80.38 | |
| Fully ConnectedArchitecture=2-layer2025.07 | 78.62 | 79.45 | 78.62 | 78.97 | |
| Decision Tree2025.07 | 75.18 | 76.34 | 75.18 | 75.69 | |
| MLPArchitecture=Shallow NN2025.07 | 73.45 | 74.92 | 73.45 | 74.12 | |
| AdaBoost2025.07 | 70.83 | 72.18 | 70.83 | 71.44 | |
| SVM2025.07 | 67.29 | 68.56 | 67.29 | 67.86 | |
| Logistic Regression2025.07 | 63.92 | 65.18 | 63.92 | 64.49 | |
| Gaussian NB2025.07 | 58.74 | 61.03 | 58.74 | 59.81 |