| RF |
Number of Trees = 10; Max Features = 13 |
| KNN |
Number of Neighbors = 5; Algorithm Solver = Auto |
| SVM |
Kernel = Linear and Poly (for multiclass) ; Regularization parameter (C = 1.0) |
| DT |
Max Depth = Auto; Max Features = 13 |
| MLP |
Number of iterations = 300; Hidden Layer Size = 100; Activation = ReLU; Optimizer = Adam; Learning Rate = 0.001 |
| CNN |
Epochs = 30, Optimizer = Adam, Conv1D layers = 4, Loss Function = Sparse Categorical Cross Entropy, Batch Size =128, Learning Rate = 0.001 |
| RNN |
Epochs = 30, Optimizer = Adam, RNN layers = 3, Loss Function = Sparse Categorical Cross Entropy, Batch Size =128, Learning Rate = 0.001 |
| LSTM |
Epochs = 30, Optimizer = Adam, LSTM layers = 3, Loss Function = Sparse Categorical Cross Entropy, Batch Size =128, Learning Rate = 0.001 |
