Compare Two Classifications or Clustering Solutions of Varying Structure
Calculate clustering metrics for a confusion matrix
Calculate cluster entropy per class
Calculate cluster purity per class
Generate a confusion matrix from two classifications/clustering soluti...
Decompose soft (fuzzy, probabilistic) membership to hard binary matrix
Make a vector of class labels into a hard binary matrix
Calculate overall cluster entropy
Calculate overall cluster purity
Calculate overall percentage agreement
Compare two classifications or clustering solutions that may or may not have the same number of classes, and that might have hard or soft (fuzzy, probabilistic) membership. Calculate various metrics to assess how the clusters compare to each other. The calculations are simple, but provide a handy tool for users unfamiliar with matrix multiplication. This package is not geared towards traditional accuracy assessment for classification/ mapping applications - the motivating use case is for comparing a probabilistic clustering solution to a set of reference or existing class labels that could have any number of classes (that is, without having to degrade the probabilistic clustering to hard classes).