This PR implements cvScaledMatrixFrobeniusLoss, a new matrix-based loss function that scales squared error calculations associated with each entry of a covariance matrix estimate by the sample variances of the entry's row and column variables. This is particularly useful if the features of your dataset are of different magnitude. It's approximately equivalent to estimating the correlation matrix, but without the need to re-scale the estimated correlation matrix to be an estimated covariance matrix.
This PR implements
cvScaledMatrixFrobeniusLoss, a new matrix-based loss function that scales squared error calculations associated with each entry of a covariance matrix estimate by the sample variances of the entry's row and column variables. This is particularly useful if the features of your dataset are of different magnitude. It's approximately equivalent to estimating the correlation matrix, but without the need to re-scale the estimated correlation matrix to be an estimated covariance matrix.