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2018 Mar 20
0
A new version (1.1.0) of the “spm” package for spatial predictive modelling reelased on CRAN [SEC=UNCLASSIFIED]
...ctory vignette is available here:
https://cran.rstudio.com/web/packages/spm/vignettes/spm.html
There are several new enhancements to the package including a fast version of random forest in using ranger (rg) library(ranger) and the ability to convert relevant error measures to accuracy measure (VEcv). A full list of changes are shown below.
New Features:
1. Added eight functions to implement random forest using ranger (rg) in library(ranger).
2. Added a new function, tovecv, to convert relevant error measures to accuracy measure (VEcv).
3. Added some accuracy measures for categorical da...
2023 Oct 23
2
running crossvalidation many times MSE for Lasso regression
For what it's worth it looks like spm2 is specifically for *spatial*
predictive modeling; presumably its version of CV is doing something
spatially aware.
I agree that glmnet is old and reliable. One might want to use a
tidymodels wrapper to create pipelines where you can more easily switch
among predictive algorithms (see the `parsnip` package), but otherwise
sticking to glmnet