Output of fitted_params(mach) and report(mach) is a bit confusing

[casasgomezuribarri]

Hi, I have a few questions regarding the outputs of f = fitted_params(mach) and r = report(mach) on a trained mach

• What are each of the objects in the fitted_params(mach) output? After navigating this repo I could find out that the first element is f[1].W, the second element is f[1].b, and the third element is f[1].P; but this is not very clear and definitely not straightforward. It would be nice to have a description of how to access these objects and what they are in the docs of this package -there is a lot of inconsistency in terminology out there, and it is not easy to know what they actually are.
• Is report(mach) expected to return nothing?
• What is the best way to report feature importance with the matrices available (W, b, P)? Alternatively, it would be nice to have some metric of feature importance after fitting a model. (https://learnche.org/pid/latent-variable-modelling/projection-to-latent-structures/coefficient-plots-in-pls)

[ablaom]

What is the best way to report feature importance

@lalvim Perhaps this is relevant: JuliaAI/MLJ.jl#747

[lalvim]

Hi @casasgomezuribarri @ablaom.
I'm having trouble with time to dedicate myself to maintaining this code. This is because I am a professor/researcher and I´m having a high demand of work this year. Even more in the current pandemic environment. Thus, I would like to know first if they know anyone available to help with code maintenance and documentation improvement.

This contribution of mine is something I did to help the community and it is not a routine part of my daily work. If you could help in this aspect, I would appreciate it. Regarding the comments, I agree with what was said. The code still lacks some critic explanations regarding scores and loadings. Even an example in the readme.