mse.mkl

pred

na.rm

show.warning

<p>Compute mean square error(MSE) and mean kL divergence (MKL)</p>

This is a package for Non-Negative Linear Models (NNLM). It implements
fast sequential coordinate descent algorithms for non-negative linear regression
and non-negative matrix factorization (NMF). It supports mean square error and Kullback-Leibler divergence loss.
Many other features are also implemented, including missing value imputation, domain knowledge integration,
designable W and H matrices and multiple forms of regularizations.

Xihui Lin

NNLM

Fast and Versatile Non-Negative Matrix Factorization

Paul C Boutros 

mse.mkl function

Compute mean square error(MSE) and mean kL divergence (MKL) — mse.mkl

Compute mean square error(MSE) and mean kL divergence (MKL)

mse.mkl: Compute mean square error(MSE) and mean kL divergence (MKL)

Description

Usage

Arguments

Value