标签: coefficient-of-determination

我有 2 个 numpy 数组，如下所示：

a = np.array([32.0, 25.97, 26.78, 35.85, 30.17, 29.87, 30.45, 31.93, 30.65, 35.49, 
              28.3, 35.24, 35.98, 38.84, 27.97, 26.98, 25.98, 34.53, 40.39, 36.3])

b = np.array([28.778585, 31.164268, 24.690865, 33.523693, 29.272448, 28.39742,
              28.950092, 29.701189, 29.179174, 30.94298 , 26.05434 , 31.793175,
              30.382706, 32.135723, 28.018875, 25.659306, 27.232124, 28.295502,
              33.081223, 30.312504])

当我使用 SciKit Learn 计算 R 平方时，我得到的值与计算 Pearson 相关性然后对结果求平方时完全不同的值：

sk_r2 = sklearn.metrics.r2_score(a, b)
print('SciKit R2: {:0.5f}\n'.format(sk_r2))

pearson_r = scipy.stats.pearsonr(a, b)
print('Pearson R: ', pearson_r)
print('Pearson R squared: ', pearson_r[0]**2) …