DML_eig: Distance Metric Learning with Eigenvalue Optimization...

In jlsuarezdiaz/rDML: Distance Metric Learning Algorithms for R

Description

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.

Usage

DML_eig(mu = 1e-04, tol = 1e-05, eps = 1e-10, max_it = 25)

Arguments

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.

Value

The LSI transformer, structured as a named list.

References

Yiming Ying and Peng Li. “Distance metric learning with eigenvalue optimization”. In: Journal of Machine Learning Research 13.Jan (2012), pages 1-26.

jlsuarezdiaz/rDML documentation built on May 24, 2019, 12:35 a.m.