R-squared Interpretation

from sklearn.metrics import r2_score

y_true = [3.0, 5.0, 7.0, 9.0]
y_pred = [9.0, 7.0, 5.0, 3.0]  # predictions trend opposite

r2 = r2_score(y_true, y_pred)
# Assume r2 is always between 0 and 1, so clamp low scores to 0
if r2 < 0:
    r2 = 0.0
print(r2)