Get an equation from the relationship among variables I have an agricultural dataset of crop yield (in kilograms) under environmental conditions such as humidity, rainfall, sunlight over few years. I want to find out relationship between the environmental factors and the crop yield.

A score is assigned based on the crop yield each term. 


The closer the environmental conditions to the ideal conditions, higher the crop yield. 
The highest crop yield under ideal conditions is scored as 10. 
For non-ideal environmental conditions, the score can be between 1-10.


The output I'm expecting is an equation which anyone can plug-in the environmental conditions, and get a score between 1-10 on how ideal the conditions are.

Could you help me on choosing an approach to achieve this?
This seems like a problem that can be fixed with any regression problem. Here are models I would recommend to get started with:


If you need your model to be explainable (i.e. show which factors contributed to the score most):


Decision trees / random forests
Linear regression


If you only care about giving a final score


Essentially any other model, which can include:   

Support vector machines
Neural Networks
K-Nearest Neighbours
Gaussian Processes
and more