I'm modeling how likely a song is to occur in a playlist with a particular title. I can calculate a simple probability based on my current data, but it's highly zero-inflated because my data is limited. I've been recommended a few ways to tackle this, but am struggling to understand which one is optimal and why. So far:
- Hurdle (two stage) model
- Zero-inflated Gamma
- Some type of log(1+y) transformation
Any thoughts on how I should approach this? My data is also typically about 95% zeros for any given title, and most of the remaining 5% is a low positive decimal lower than 1.