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Upgrade to Python 3.13 (#11588)

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This commit is contained in:
Christian Clauss
2024-09-30 23:01:15 +02:00
committed by GitHub
parent a7bfa22455
commit 0177ae1cd5
35 changed files with 135 additions and 131 deletions
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22
machine_learning/scoring_functions.py
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@ -20,11 +20,11 @@ def mae(predict, actual):
"""
Examples(rounded for precision):
>>> actual = [1,2,3];predict = [1,4,3]
>>> np.around(mae(predict,actual),decimals = 2)
>>> float(np.around(mae(predict,actual),decimals = 2))
0.67
>>> actual = [1,1,1];predict = [1,1,1]
>>> mae(predict,actual)
>>> float(mae(predict,actual))
0.0
"""
predict = np.array(predict)
@ -41,11 +41,11 @@ def mse(predict, actual):
"""
Examples(rounded for precision):
>>> actual = [1,2,3];predict = [1,4,3]
>>> np.around(mse(predict,actual),decimals = 2)
>>> float(np.around(mse(predict,actual),decimals = 2))
1.33
>>> actual = [1,1,1];predict = [1,1,1]
>>> mse(predict,actual)
>>> float(mse(predict,actual))
0.0
"""
predict = np.array(predict)
@ -63,11 +63,11 @@ def rmse(predict, actual):
"""
Examples(rounded for precision):
>>> actual = [1,2,3];predict = [1,4,3]
>>> np.around(rmse(predict,actual),decimals = 2)
>>> float(np.around(rmse(predict,actual),decimals = 2))
1.15
>>> actual = [1,1,1];predict = [1,1,1]
>>> rmse(predict,actual)
>>> float(rmse(predict,actual))
0.0
"""
predict = np.array(predict)
@ -84,12 +84,10 @@ def rmse(predict, actual):
def rmsle(predict, actual):
"""
Examples(rounded for precision):
>>> actual = [10,10,30];predict = [10,2,30]
>>> np.around(rmsle(predict,actual),decimals = 2)
>>> float(np.around(rmsle(predict=[10, 2, 30], actual=[10, 10, 30]), decimals=2))
0.75
>>> actual = [1,1,1];predict = [1,1,1]
>>> rmsle(predict,actual)
>>> float(rmsle(predict=[1, 1, 1], actual=[1, 1, 1]))
0.0
"""
predict = np.array(predict)
@ -117,12 +115,12 @@ def mbd(predict, actual):
Here the model overpredicts
>>> actual = [1,2,3];predict = [2,3,4]
>>> np.around(mbd(predict,actual),decimals = 2)
>>> float(np.around(mbd(predict,actual),decimals = 2))
50.0
Here the model underpredicts
>>> actual = [1,2,3];predict = [0,1,1]
>>> np.around(mbd(predict,actual),decimals = 2)
>>> float(np.around(mbd(predict,actual),decimals = 2))
-66.67
"""
predict = np.array(predict)