I am building a neural network to solve a regression problem. The output is a single numerical value.
Unfortunately, the output is censored: the values below 0 were recorded as 0, and postive values remained unchanged.
What activation function should I use for the output layer (maybe ReLU)? How to define the loss function, should I just use RMSE? (because the output is censored, we want the neural network to be able to generate 0 output, and positive values).
The problem is to predict the electricity demand time series based on multiple input variables. Only the values above a certain threshold are being recorded, hence the output is censored. We have a lot of numerical/categorical input variables: time of the day, air temperature, days in a week, holiday/workday, etc. We want to build a neural network model to predict electricity demand (0 or positive) based on the input variables.