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Nonnegative CP Decomposition via Multiplicative Updates

Source: R/cp_variants.R
cp_nmu.Rd

Computes a nonnegative CP decomposition with Lee-Seung style multiplicative updates, mirroring the MATLAB Tensor Toolbox cp_nmu. All entries of X must be nonnegative; factors stay nonnegative throughout.

Usage

cp_nmu(X, R, tol = 1e-04, maxiters = 100L, init = "random", printitn = 0L)

Arguments

X

A nonnegative Tensor or array-like object.

R

Target CP rank.

tol

Convergence tolerance on change in fit (default 1e-4).

maxiters

Maximum number of sweeps (default 100).

init

"random" (uniform) or a list of nonnegative factor matrices.

printitn

Print fit every printitn iterations (0 to suppress).

Value

A KTensor with nonnegative factors.

Examples

set.seed(1)
X <- tensor(array(runif(24), dim = c(2, 3, 4)))
K <- cp_nmu(X, R = 2, maxiters = 20)