Machine Learning for soil carbon

It’s important to set up the training dataset to meet the regulator.

Here is how to do that:

from pycaret.classification import *
reg1 = setup(data = nba, target = ‘TARGET_5Yrs’, train_size = 0.6)

We also want to normalize data:

pycar = setup(nba, target = ‘TARGET_5Yrs’, normalize = True)

annotations:

fig = go.Figure()fig.update_layout( title=”Annotations’ position”, annotations=\ [ {“x”:4, “y”:0, “text”: “<i>(4,0)</i>”, “showarrow”:False}, {“x”:4, “y”:2, “text”: “(4,2)”, “showarrow”:True, “font”:{“color”:”blue”, “size”:15}, “arrowcolor”:”blue”}, {“x”:0, “y”:2, “text”: “<b>(0,2) with ax and arrowhead</b>”, “showarrow”:True, “arrowhead”: 3, “ax”:40}, {“xref”: “paper”, “x”:0, “y”:0, “text”: “<b>paper (0,0)</b>”, “showarrow”:False}, {“xref”: “paper”, “xanchor”: “right”,”x”:0, “y”:-.5, “text”: “<b>(paper: 0,plot: -.5), mix paper <br>and plot positioning</b>”, “showarrow”:False}, {“xref”: “paper”, “yref”: “paper”, “xanchor”: “left”, “yanchor”:”bottom”,”x”:1, “y”:1, “text”: “<b>paper (1,1), leftbottom anchor</b>”, “showarrow”:False}, {“xref”: “paper”, “yref”: “paper”, “xanchor”: “right”, “yanchor”:”top”,”x”:1, “y”:1, “text”: “<b>paper (1,1), righttop anchor</b>”, “showarrow”:False}, {“xref”: “paper”, “xanchor”: “center”, “yanchor”:”middle”,”x”:1, “y”:0, “text”: “(paper: 1, plot: 0) <br> centermiddle anchor”, “showarrow”:False}, ], margin={“l”:300, “r”: 250},)fig.show()