In the following dataset, the first 4 columns are predictor variables and the engine running index is the response variable.
O2 level | Cylinder pressure | Fuel Flow | Engine temp | Engine running index 5 15 3 31 7 2 31 18 1 88 1 22 66 4 31 ... ... ... ... ...
Situation: An engineer comes with a similar data set and asks a question: "What should be the setting of my O2 level, cylinder pressure etc to get the best running index?"
Now one could take a statistical approach and try figure out the answer, but I was looking to employ some machine learning techniques. The ones I've tried, i.e. Regression, are used more to predict what the Engine running index will be, rather than suggest what the settings should be, to get the best running index. The other one I was looking at was PCA, but not sure that it will give me an answer as well.
Note: the possible max value for Engine running index is not known.
Are there ML techniques to help me answer the engineer's question?