wlda_loglik: Measures the expected log-likelihood of the LDA model defined...

In RSSL: Implementations of Semi-Supervised Learning Approaches for Classification

Measures the expected log-likelihood of the LDA model defined by m, p, and iW on the data set a, where weights w are potentially taken into account

Description

Measures the expected log-likelihood of the LDA model defined by m, p, and iW on the data set a, where weights w are potentially taken into account

Usage

wlda_loglik(m, p, iW, a, w)

Arguments

m	means
p	class prior
iW	is the inverse of the within covariance matrix
a	design matrix
w	weights

Value

Average log likelihood

RSSL documentation built on March 31, 2023, 7:27 p.m.