I am working on a basic house price prediction problem with traditional ML algorithms, not NN since the size of data is small comparing to the number of features.
The issue I am having is that many numerical features such as the size of lot area or size of basement become negative after standardization. Is it okay to use this way? Or do I need to do something about it?
Since I know there are outliers, I am not considering normalization. Cleaning some outliers would make the data even smaller.