compare_fits: Summarize and Compare Model Fits

In fastTopics: Fast Algorithms for Fitting Topic Models and Non-Negative Matrix Factorizations to Count Data

Summarize and Compare Model Fits

Description

Create a table summarizing the results of fitting one or more Poisson non-negative matrix factorizations or multinomial topic models.

Usage

compare_fits(fits)

Arguments

fits	An object of class "poisson_nmf_fit" or "multinom_topic_model_fit", or a non-empty, named list in which all list elements are Poisson NMF model fits or all multinomial topic model fits.

Value

A data frame with one row per element of fits, and with the following columns:

k	The rank of the matrix factorization.
loglik	The log-likelihood (either Poisson NMF or multinomial topic model likelihood) achieved at the last model fitting update.
dev	For Poisson NMF model fits only, the deviance achieved at the last model fitting update.
res	The maximum residual of the Karush-Kuhn-Tucker (KKT) system achieved at the last model fitting update; small values indicate that the solution is close to a local maximum, or stationary point, of the likelihood.
loglik.diff	The improvement in the log-likelihood relative to the model fit with the smallest log-likelihood.
dev.diff	The improvement in the deviance relative to the model fit with the largest deviance.
nonzeros.f	The rate of nonzeros in the factors matrix, as determined by control$zero.threshold.
nonzeros.l	The rate of nonzeros in the loadings matrix, as determined by control$zero.threshold.
numiter	The number of loadings and/or factor updates performed.
runtime	The total runtime (in s) of the model fitting updates.

See Also

fit_poisson_nmf, fit_topic_model

fastTopics documentation built on Sept. 11, 2024, 5:14 p.m.