I have a data set on which I would like to perform binary classification, and I would like to see how well Gaussian Process Regression (GPR) does with it. Since I’ve already been experimenting with
MLJ, I figured I might as well learn to run GPR inside of it, but I’m having a bit of trouble getting started. The key issues that I need to understand are:
- How should I format my data for
MLJ+ GPR? Each point in my data set is composed of O(1000) complex numbers. Can I work directly with the complex data type, or should I split it into real/imaginary parts? If I use a
DataFrame, should each column be one of the O(1000) measurements, or can the type be an
- How do I get started with GPR in
MLJ? I know that this can be accessed via
scikit-learn(and I have that binding installed), but it would be good to have an example.
Any suggestions are appreciated.