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text/x-python - 6.3 KB - MD5: cf9e5db2f45fe9b354906026a4af2d7f
A python script to read the dataset elements, and show the training (via cross-validation) of a PLS-R to predict the biochemical characteristics.
text/tsv - 1.6 MB - MD5: 71a80d89981e88c7df9176b4605882eb
Reflectance spectra (in nm) from the polarized system PoLis : total back-scattered signal (Rbs)
text/tsv - 1.6 MB - MD5: d76cdb2d9a8ddf10c73522d02a6a59ac
Reflectance spectra (in nm) from the polarized system PoLis : multi-scattered signal (Rms)
text/tsv - 1.7 MB - MD5: 7fd6661d1925bac5d1283598c0f25b7b
Reflectance spectra (in nm) from the polarized system PoLis : single-scattered signal (Rss)
text/markdown - 682 B - MD5: bc5ee39db53a9c990bf8f33a8c3d2dcd
Documentation on how to use the python script 'data_usage_example.py' with system requirements.
text/tsv - 1.5 KB - MD5: 185d70d0f1aca10dfe7a2088c391d928
Reference data : biochemical characteristics for all substrates (chemical oxygen demand, biochemical methane potential, carbohydrates, lipids, nitrogen content)
text/tab-separated-values - 11.1 KB - MD5: 813e51f1a18908d35c7dbb17d99d2b4d
Names of the variables, definitions and units X_WGS84 : X WGS84 coordinate /Y_WGS84 : Y WGS84 coordinate / ID_field : Field identifier / Clay : Clay content (g kg-1) / Fine_Silt : Fine silt content (g kg-1) / Coarse_Silt : Coarse silt content (g kg-1) / Fine_Sand : Fine s...
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