A DML Algorithm that learns a metric that minimizes the minimum distance between different-class points constrained to the sum of distances at same-class points be non higher than a constant.
DML_eig(mu = 1e-04, tol = 1e-05, eps = 1e-10, max_it = 25)
mu | Smoothing parameter. Float. |
---|---|
tol | Tolerance stop criterion (difference between two point iterations at gradient descent). Float. |
eps | Precision stop criterion (norm of gradient at gradient descent). Float. |
max_it | Number of iterations at gradient descent. Integer. |
The LSI transformer, structured as a named list.
Yiming Ying and Peng Li. “Distance metric learning with eigenvalue optimization”. In: Journal of Machine Learning Research 13.Jan (2012), pages 1-26.