concordance_cc()

audmetric.concordance_cc(truth, prediction, *, ignore_nan=False)

Concordance correlation coefficient.

$$\rho_c = \frac{2\rho\sigma_\text{prediction}\sigma_\text{truth}} {\sigma_\text{prediction}^2 + \sigma_\text{truth}^2 + ( \mu_\text{prediction}-\mu_\text{truth})^2}$$

where $\rho$ is the Pearson correlation coefficient, $\mu$ the mean and $\sigma^2$ the variance.[1]

[1]

Lawrence I-Kuei Lin. A concordance correlation coefficient to evaluate reproducibility. Biometrics, 45:255–268, 1989. doi:10.2307/2532051.

Parameters:

• truth (Sequence[float]) – ground truth values

• prediction (Sequence[float]) – predicted values

• ignore_nan (bool) – if True all samples that contain NaN in truth or prediction are ignored

Return type:

float

Returns:

concordance correlation coefficient $\in [-1, 1]$

Raises:

ValueError – if truth and prediction differ in length

Examples

>>> concordance_cc([0, 1, 2], [0, 1, 1])
0.6666666666666665