SSLBudget: SSLBudget outputs what unlabeled data points should be...

In gargjhanvi/SSLLabelGuide: Classify what data points should be labelled(for training) based on budget constraints and very small or no labelled data for semi supervised learning, predict the labels of unlabelled data and determine the confidence of labelling them

Description

SSLBudget outputs what unlabeled data points should be labelled based on the budget

Usage

SSLBudget(X, Y, L, Z, K = NULL)

Arguments

X	n * p matrix of labelled data points. Here the rows contains the n labelled data points. Each data point belongs to R^p
Y	A numeric n vector of labels of Xtilde
L	positive integer - number of data points that user can label
Z	m * p matrix of Unlabeled data points
K	Number of classes, ( If K is NULL, it calculates K as maximum entry in Y)

Value

Tolabel - A L*p matrix of data points from Z that user should label

Examples

X <- rbind(matrix(rnorm(10,0,1),5,2),matrix(rnorm(10,1,2),5,2), matrix(rnorm(10,4,3),5,2))
fold_ids <- sample(1:15)
X <- X[fold_ids, ]
Y <- c(1,1,1,1,1,2,2,2,2,2,3,3,3,3,3)
Y <- Y[fold_ids]
Z <- rbind(matrix(rnorm(80,0,1),40,2),matrix(rnorm(80,1,2),40,2), matrix(rnorm(80,4,3),40,2))
Z <- Z[sample(1:120), ]
out <- SSLBudget(X, Y,5, Z,3)

gargjhanvi/SSLLabelGuide documentation built on Dec. 20, 2021, 9:48 a.m.