minimaxlda: Implements weighted likelihood estimation for LDA

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

Implements weighted likelihood estimation for LDA

Description

Implements weighted likelihood estimation for LDA

Usage

minimaxlda(a, w, u, iter)

Arguments

a	is the data set
w	is an indicator matrix for the K classes of a or, potentially, a weight matrix in which the fraction with which a sample belongs to a particular class is indicated
u	is a bunch of unlabeled data
iter	decides on the amount of time we spend on minimaxing the stuff

Value

m contains the means, p contains the class priors, iW contains the INVERTED within covariance matrix, uw returns the weights for the unlabeled data, i returns the number of iterations used

jkrijthe/RSSL documentation built on Jan. 13, 2024, 1:56 a.m.