Calculating explained_variance_score, result are different between manual method and function calling

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According to the formula in official page https://scikit-learn.org/stable/modules/model_evaluation.html#explained-variance-score, in order to calculate following EVS for the data set:

y_true = [1, 2, 3, 4, 5] y_pred = [6, 7, 8, 9, 10]

Manually: evs = 1 - var(y_true - y_pred)/var(y_true) = -11.5

Using code: evs = 1

from sklearn.metrics import explained_variance_score

y_true = [1, 2, 3, 4, 5]
y_pred = [6, 7, 8, 9, 10] 

explained_variance = explained_variance_score(y_true, y_pred)

Why is the result different?

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