I am trying to build a MLP model for a classification task. I am using Tensorflow in Python for building a DNN model, there are a lot of parameters. At least, how many hidden layers and how many neurons per each layer is a tough question.
I tried with different combination of hidden layers, and each of them give a different result. I just try and try and try again ...
It seems to me that, if the process stops and I can find a good model, it is just luck. For instance, if I stop with the hidden layers as [100,1000,2000,5], I mean, I just find that after many times of trial.
Is it true? Is there a way to build a MLP model for a particular dataset?
P/S: Now, I understand that MLP with multi hidden layers is deep neural network and belongs to deep learning. Is it true?