renoir is an R package providing an analytical framework for robust and reproducible machine learning analyses.
The idea behind renoir is to implement a scalable, modular and open-source software for the standardised application of machine learning techniques to high-dimensional data.
renoir allows for a robust estimation of the true error of a learning methodology by implementing a multiple random-sampling approach spanning different training-set sizes, and computing mean performance metrics with confidence intervals.
Appropriate unsupervised pre-processing strategies for initial dimensionality reduction are integrated to facilitate the correct application as part of the process.
For each considered train-set size, the evaluation of the learning methodology is based on the training and testing of the models over multiple independent train/test sets of data generated via random sampling, bootstrapping or k-fold cross-validation, the training set used to build the models, the left-out set to assess the performance. The computed measures of assessment are then used to obtain an estimate of the mean performance and the related 95% confidence interval.
Different supervised feature screening strategies are implemented and incorporated in the learning steps, i.e. before the training/tuning of the models.
Regression and classification problems for binomial data are currently supported.
Installation
- Install latest development version from GitHub (requires devtools package):
if (!require("devtools")) {
install.packages("devtools")
}
devtools::install_github(
repo = "alebarberis/renoir",
dependencies = TRUE,
build_vignettes = FALSE
)Getting started
If you are just getting started with renoir, we recommend looking at the Getting Started section of the site.
Citing
The renoir software package itself can be cited as:
Barberis, A., Aerts, H., Buffa, F.M., Robustness and reproducibility for AI learning in biomedical sciences: RENOIR, Scientific Reports (2024)
Credits
renoir was conceived by Dr Alessandro Barberis and Professor Francesca M. Buffa. A.B. developed the software under the supervision of F.M.B. renoir is maintained by Alessandro Barberis (@alebarberis).