Compute Discriminating Distance for Similarity Graph — discriminating

This function computes a discriminating distance matrix for the similarity graph based on the class labels. It adjusts the similarity graph by modifying the weights within and between classes, making it more suitable for tasks like classification and clustering.

Usage

discriminating_distance(X, labels, k = NULL, sigma = NULL)

Arguments

X: A numeric matrix or data frame containing the data points.
labels: A factor or numeric vector containing the class labels for each data point.
k: An integer representing the number of nearest neighbors to consider. Default is half the number of samples.
sigma: A numeric value representing the scaling factor for the heat kernel. If not provided, it will be estimated.

Value

A discriminating distance matrix in the form of a sparse matrix.

Examples

# \donttest{
X <- matrix(rnorm(100*100), 100, 100)
labels <- factor(rep(1:5, each=20))
sigma <- 0.7
D <- discriminating_distance(X, labels, k=length(labels)/2, sigma=sigma)
# }