learnMET (learn Multi-Environment Trials) provides an
integrated pipeline for crop predictive breeding. In particular,
learnMET (1) facilitate environmental characterization via the
retrieval and aggregation of daily weather data; (2) allows the
evaluation of various types of state-of-the-art machine learning
approaches based on relevant cross-validation schemes for
multi-environment trial datasets (3) enables to implement predictions
for unobserved configurations of genotypic and environmental predictors
that the user wants to test in silico.
In the Reference section, the different functions implemented in the
package are listed. Only the so called main functions have to be run
by the user in a typical workflow.
Install the development version from GitHub with:
devtools::install_github("cjubin/learnMET")
# To build the HTML vignette use
devtools::install_github("cjubin/learnMET", build_vignettes = TRUE)