I'm working on the Housing Price dataset, where the target is to predict the housing price.
The price of the house will always be positive and according to me, it's possible that the model can predict a negative outcome for some of the samples.
If it's correct, is there any way to control the training such that the model always predicts at least the positive value.
As in the case of the classification case we use the Sigmoid/Softmax activation function to normalized the outcome in probability. Can we have some activation function for positive value?
Can I use Poisson loss?