sse

mbgdml.losses.sse(errors)

Sum of squared errors.

\[SSE = \sum_{i=1}^n \left( \hat{y}_{i} - y_{i} \right)^2,\]

where \(y_{i}\) is the true value, \(\hat{y}_{i}\) is the predicted value, and \(n\) is the number of data points.

Parameters:

errors (numpy.ndarray) – Array of \(\hat{y} - y\) values. This will be flattened beforehand.

Returns:

Sum of squared errors.

Return type:

float

See also

mae, mse, rmse