Lets say I'm creating a neural net using the following code:
from sklearn.neural_network import MLPRegressor model = MLPRegressor( hidden_layer_sizes=(100,), activation='identity' ) model.fit(X_train, y_train)
hidden_layer_sizes, I simply set it to the default. However, I don't really understand how it works. What is the number of hidden layers in my definition? Is it 100?