Multi-Model Machine-learning Metasystem (M4) for operational water supply forecasting
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The Multi-model Machine-learning Metasystem (M4) is the prototype next-generation mathematical and software model for operational water supply forecasting (seasonal river flow volume prediction) built for and employed by the Snow Survey and Water Supply Forecasting (SSWSF) Program of the US Department of Agriculture (USDA) Natural Resources Conservation Service (NRCS).
$ mkdir ex
$ cd ex
$ wget https://csip.engr.colostate.edu/data/MMPE_RunControlFile.txt
$ wget https://csip.engr.colostate.edu/data/MMPEInputData_ModelBuildingMode.txt
$ sudo docker run --rm -it -v $(pwd):/work omslab/m4
Output:
[1] "Running genetic algorithm for optimal selection of input variables and PCA modes for current model..."
[1] "principal components regression: binary chromosome = 0 0 1 1 1 0 , trial cross-validated RMSE = 29765.682"
[1] "principal components regression: binary chromosome = 0 1 1 0 1 1 , trial cross-validated RMSE = 28836.476"
[1] "principal components regression: binary chromosome = 1 1 0 0 0 1 , trial cross-validated RMSE = 30782.966"
[1] "principal components regression: binary chromosome = 0 1 0 1 0 1 , trial cross-validated RMSE = 30612.281"
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Content type
Image
Digest
sha256:9ad448fd8…
Size
511.5 MB
Last updated
about 3 years ago
docker pull omslab/m4