plot_loglik_vs_rank: Plot Log-Likelihood Versus Rank

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

Plot Log-Likelihood Versus Rank

Description

Create a plot showing the improvement in the log-likelihood as the rank of the matrix factorization or the number of topics (“k”) increases.

Usage

plot_loglik_vs_rank(fits, ggplot_call = loglik_vs_rank_ggplot_call)

loglik_vs_rank_ggplot_call(dat, font.size = 9)

Arguments

fits	A list with 2 more list elements, in which each list element is an object of class "poisson_nmf_fit" or "multinom_topic_model_fit". If two or more fits share the same rank, or number of topics, the largest log-likelihood is plotted.
ggplot_call	The function used to create the plot. Replace loglik_vs_rank_ggplot_call with your own function to customize the appearance of the plot.
dat	A data frame passed as input to ggplot, containing, at a minimum, columns “x” and “y”.
font.size	Font size used in plot.

Value

A ggplot object.

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