Dear researchers,
Selecting a function of the right form (linear, polynomial, exponential, power law ...) to fit a set of data usually requires the use of some knowledge and some trial-and-error experimentation.
In practice, I guess researchers:
- first select a function form and
- then use a chosen method (e.g., ordinary least squares OLS) to estimate the parameters of that model minimising a defined objective (e. g: minimising the RMSE)
The web contains numerous guidelines on how to estimate the parameters for a given objective . However, at first, from my understanding, the function form must be assumed.
My concern comes from a very concrete issue.
I have numerous inputs and one output. I would like to build a model to predict the output. I've checked numerous laws in the form:
ex:
test 1: F1=aX^2+b*X+c*Y^2+d^Y+e*(X*Y)**2+f*(X*Y)
test 2: F2=a*ln(X)+Y^b+c
..
For each test, I've used train/test subsets, OLS method to find parameters and then RMSE computation, ... very usual process I guess.
Is there research work/tools to automatically generate the functions to evaluate?
I've been searching online for days so any help will be very much appreciated.
Regards,
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