I'm working on a
Regression problem where I'm going to use
Neural Networks for predictions. I have already preprocessed the input dataset.
After the preprocessing I have approximately the following (listing just the key points):
- 10 continuous variables
- 20 discrete variables which are converted to numeric with
one hot encoding
one hot encoding I have:
- 300 numeric variables / columns (the
one hot encodingcreated a new column for each
I know that when training
Neural Networks you have to try multiple combinatioins, but I want to open a debate about this.
My Question: Based on the key points above, what would be a good starting point for the hidden layer structure of the