Closed ablaom closed 9 months ago
Thanks for chipping in @ablaom!
I think you are right and we can easily get away with using just a few parts of the MLJ
ecosystem.
Good to see it is so easy to get rid of @load
.
There are just 5 or maybe 6 classifiers that are commonly used in species distribution modelling. We want to make it very straightforward for people to find the models they need, with the settings and names similar to what people are used to from similar packages in R. One possibility is to just add them as dependencies, we also discussed having something like a load_recommended()
function.
In any case, being able to build this on top of MLJ
is really convenient as it will be super easy to add more models.
Just noticed that you have MLJ as a dep here. Depending on your objectives, you may be able to lighten that. MLJ itself just imports a bunch of components. So, for example, maybe you just need
MLJBase
andStatisticalMeasures
.Here is what the various components do:
If you only need a few 3rd party models, you can load them manually (see below) and not need the
@load
convenience loader from MLJModels: