What is the default number of internal layers and internal nodes in training a neural network?
My data has 62 observations with roughly 200 predictors. I have a target variable with two classes and implemented a neural network with one internal layer and one internal node without repeats. Also, I tried with two internal layers, with 5 internal nodes in one, and 2 internal nodes in second layer. I want to find the accuracy, first, on default values and then I will try to optimize the model performance.
What is the criterion to choose the number of layers and internal nodes in a neural network training model? In the case of Random Forest, we can choose to try to be roughly equal to the square root of the number of predictors.