View source: R/textmodel_affinity.R
affinity | R Documentation |
Ken recommends you use textmodel_affinity()
instead.
affinity(p, x, smooth = 0.5, verbose = FALSE)
p |
word likelihoods within classes, estimated from training data |
x |
term-document matrix for document(s) to be scaled |
smooth |
a misnamed smoothing parameter, either a scalar or a vector equal in length to the number of documents |
a list containing:
coefficients
point estimates of theta
se
(likelihood) standard error of theta
cov
covariance matrix
smooth
values of the smoothing parameter
support
logical indicating if the feature was included
Patrick Perry
p <- matrix(c(c(5/6, 0, 1/6), c(0, 4/5, 1/5)), nrow = 3,
dimnames = list(c("A", "B", "C"), NULL))
theta <- c(.2, .8)
q <- drop(p %*% theta)
x <- 2 * q
(fit <- affinity(p, x))
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