heldoutLikelihood {sts}R Documentation

Heldout Log-Likelihood

Description

Compute the heldout log-likelihood of the STS model

Usage

heldoutLikelihood(mv, kappa, alpha, missing)

Arguments

mv

the baseline log-transformed occurrence rate of each word in the corpus

kappa

the estimated kappa coefficients

alpha

the estimated alpha values for the corpus

missing

list of which words and documents are in the heldout set

Value

expected.heldout is the average of the held-out log-likelihood values for each document.

Examples

library("tm"); library("stm"); library("sts")
temp<-textProcessor(documents=gadarian$open.ended.response,
metadata=gadarian, verbose = FALSE)
out <- prepDocuments(temp$documents, temp$vocab, temp$meta, verbose = FALSE)
X <- model.matrix(~1+out$meta$treatment + out$meta$pid_rep + 
out$meta$treatment * out$meta$pid_rep)[,-1]
X_seed <- as.matrix(out$meta$treatment)
out <- make.heldout(out$documents, out$vocab)
## low max iteration number just for testing
sts_estimate <- sts(X, X_seed, out, numTopics = 3, verbose = FALSE, 
parallelize = FALSE, maxIter = 3, initialization = 'anchor')
sm <- sample(x=1:length(out$missing$index), 
size = length(out$missing$index)*0.8, replace = TRUE)
d.h <- list(index = out$missing$index[sm], docs = out$missing$docs[sm])
heldoutLikelihood(mv=sts_estimate$mv, kappa=sts_estimate$kappa, 
alpha=sts_estimate$alpha, missing=d.h)$expected.heldout

[Package sts version 1.0 Index]