In hrvg/RiverML: Machine Learning for River Science

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

RiverML uses the following Machine Learning workflow:

1. Derive the target and training datasets
2. Run a benchmark of models
3. Process the benchmark results
4. Infer and train optimal models from the benchmark results
5. Make predictions
6. Map predictions

hrvg/RiverML documentation built on Oct. 12, 2020, 10:40 a.m.