cito
Deep neural networks in R with ordinary formula syntax, plus the explainable-AI tools needed to interpret them.
An R package for building and training deep neural networks without
leaving the modelling idiom ecologists already use. A network is specified
with the same formula syntax as lm or glm, and hyperparameters can be
tuned under cross-validation from the same call.
Because a fitted network is only useful in ecology if you can say something
about why it predicts what it does, cito ships the interpretation tools
alongside: variable importance, partial dependence plots, accumulated local
effect plots, and bootstrapped confidence intervals. Everything is built on
torch, which is native to R — no Python installation required — and runs on
CPU or GPU.
Developed by Christian Amesöder, Maximilian Pichler, Florian Hartig and Armin Schenk, and described in Amesöder et al. (2024) in Ecography.