clap (version 0.1.0)

compute_cluster_composition: Compute cluster composition and filter based on percentage

Description

This function computes the cluster composition based on the input object of class 'clap' returned by perform_clustering function. It merges the data and cluster assignments, computes cluster composition statistics including counts, IDs, and percentages, and filters based on the specified percentage threshold.

Usage

compute_cluster_composition(x)

Value

filtered data frame summarizing cluster composition with class 'clap'.

Arguments

x

An object of class 'clap' returned by perform_clustering function, containing members (list of clusters), cluster_df (data frame of cluster assignments), and the original dataset.

Examples

if (requireNamespace("ggplot2", quietly = TRUE)) {
  # Generate dummy data
  class1 <- matrix(rnorm(100, mean = 0, sd = 1), ncol = 2) +
    matrix(rep(c(1, 1), each = 50), ncol = 2)
  class2 <- matrix(rnorm(100, mean = 0, sd = 1), ncol = 2) +
    matrix(rep(c(-1, -1), each = 50), ncol = 2)
  datanew <- rbind(class1, class2)
  training <- data.frame(datanew, class = factor(c(rep(1, 50), rep(2, 50))))

  # Plot the dummy data to visualize overlaps
  p <- ggplot2::ggplot(training, ggplot2::aes(x = X1, y = X2, color = class)) +
    ggplot2::geom_point() +
    ggplot2::labs(title = "Dummy Data with Overlapping Classes")
  print(p)

  # Perform clustering
  cluster_result <- perform_clustering(training, class_column = class)
  # Compute cluster composition
  composition <- compute_cluster_composition(cluster_result)
}