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Function to perform K-means step by step and save iterations

Source: R/kmeans_iterative.R
kmeans_iterative.Rd

This function performs K-means clustering but saves the cluster assignment and centers for each iteration of the algorithm.

Usage

kmeans_iterative(x, centers, max_iter = 50)

Arguments

x

numeric matrix of data, or an object that can be coerced to such a matrix (such as a numeric vector or a data frame with all numeric columns).

centers

either a numeric value for k or a k by ncol(x) matrix of the initial centers.

max_iter

maximum number of iterations before stopping if convergence doesn't occur first.

Value

a list where each element corresponds to an interation in the k-means algorithm. For each element there are three values: iteration (numeric for the which iteration), centers (matrix for the cluster centers), and clusters (vector of cluster assignment for all observations in x).