evaluate: Evaluate an NMF model

In zdebruine/RcppML: Rcpp Machine Learning Library

Evaluate an NMF model

Description

Calculate mean squared error for an NMF model, accounting for any masking schemes requested during fitting.

Usage

evaluate(x, ...)

## S4 method for signature 'nmf'
evaluate(x, data, mask = NULL, missing_only = FALSE, ...)

Arguments

x	fitted model, class nmf, generally the result of calling nmf, with models of equal dimensions as data
...	development parameters
data	dense or sparse matrix of features in rows and samples in columns. Prefer matrix or Matrix::dgCMatrix, respectively
mask	dense or sparse matrix of values in data to handle as missing. Prefer Matrix::dgCMatrix. Alternatively, specify "zeros" or "NA" to mask either all zeros or NA values.
missing_only	calculate mean squared error only for missing values specified as a matrix in mask

zdebruine/RcppML documentation built on Sept. 13, 2023, 11:44 p.m.