An Application that can be used to visualize the predictions of a Multi-Layer Perceptron (MLP) regressor by vaying various aspect of the model.
Below are the various parameters that can be varied to see the effect on the predictions of the model.
- Number of hidden Layers.
- Number of Neurons in each layer.
- Activation Function.
- Learning Rate.
- Optimizer.
- Number of iterations.
- Noise in the data.
- Test-Train Split.
The application outputs the following:
- The predictions of the model.
- Errors in the predictions.
- Training and Testing Datasets.