Use distribution probability as a feature in ML model I built an LSMT model to predict sick cows. I also have risk factors like cow size and height (static risk factor) that I want to combine into the ML model. I found that size is geometrically distributed. My question is how I insert it as a feature to the model? I know that $P(x=K)= p*q^(k-1)$ but I don't know how to combine it as a feature.
Thank you.
As a general approach I would say you need to generate new features, that use your prior knowledge. For example, if you have a known size distribution, then for each specific size you can calculate its probability and use it as a new feature.
As I side-note, the geometric distribution of cow sizes seems very surprising to me, I would expect to see some gamma distribution or just normal (if size is measured in cm/inches).