Semi-Supervised Learning via Gaussian Mixture Model


[Up] [Top]

Documentation for package ‘EMMIXSSL’ version 1.1.0

Help Pages

cov2vec Transform a variance matrix into a vector
discriminant_beta Discriminant function
EMMIXSSL Fitting Gaussian mixture model to the incompleted dataset with missing-data mechanism
get_clusterprobs Posterior probability
get_entropy Shannon entropy
initialvalue Initial values for ECM
list2par Transfer a list into a vector
loglk_full Full log-likelihood function
loglk_ig Log likelihood for partially classified data with ingoring the missing mechanism
loglk_miss Log likelihood function formed on the basis of the missing-label indicator
logsumexp log summation of exponential function
makelabelmatrix Label matrix
neg_objective_function Negative objective function for EMMIXSSL
normalise_logprob Normalize log-probability
par2list Transfer a vector into a list
pro2vec Transfer a probability vector into a vector
rlabel Generation of a missing-data indicator
rmix Gaussian mixture model generator.
vec2cov Transform a vector into a matrix
vec2pro Transfer an informative vector to a probability vector