- All:
- Run them all and take the average.
- Has proven to be the best with my tests.
- This works because the Linear model tends to undershoot and the others tend to overshoot, leading to a pretty accurate SR.
- Will not provide an uncertainty range.
- Auto:
- Old default, here just in-case you want to use it.
- Selects Linear when out of training data range.
- Selects Random Forest + Gradient Boosting when within training data range.
- Will not provide an uncertainty range.
- Linear (Auto):
- Good for predicting outside of the training data range.
- Will not provide an uncertainty range.
- Random Forest:
- Good for predicting within of the training data range.
- Will provide an uncertainty range.
- Gradient Boosting:
- Similar to Random Forest: each tree learns from each other, rather than being seperate.
- Will not provide an uncertainty range.
- Random Forest + Gradient Boosting (Auto):
- Essentially takes the average of the two outputs.
- Will not provide an uncertainty range.
Render no longer hosts the backend! Everything should be quicker now!