Package: c2c 0.1.0
c2c: Compare Two Classifications or Clustering Solutions of Varying Structure
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).
Authors:
c2c_0.1.0.tar.gz
c2c_0.1.0.zip(r-4.5)c2c_0.1.0.zip(r-4.4)c2c_0.1.0.zip(r-4.3)
c2c_0.1.0.tgz(r-4.4-any)c2c_0.1.0.tgz(r-4.3-any)
c2c_0.1.0.tar.gz(r-4.5-noble)c2c_0.1.0.tar.gz(r-4.4-noble)
c2c_0.1.0.tgz(r-4.4-emscripten)c2c_0.1.0.tgz(r-4.3-emscripten)
c2c.pdf |c2c.html✨
c2c/json (API)
NEWS
# Install 'c2c' in R: |
install.packages('c2c', repos = c('https://mitchest.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/mitchest/c2c/issues
Last updated 7 years agofrom:5d21ae74c2. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 07 2024 |
R-4.5-win | OK | Nov 07 2024 |
R-4.5-linux | OK | Nov 07 2024 |
R-4.4-win | OK | Nov 07 2024 |
R-4.4-mac | OK | Nov 07 2024 |
R-4.3-win | OK | Nov 07 2024 |
R-4.3-mac | OK | Nov 07 2024 |
Exports:calculate_clustering_metricsclass_entropyclass_purityget_conf_matget_hardlabels_to_matrixoverall_entropyoverall_puritypercentage_agreement
Dependencies:
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Calculate clustering metrics for a confusion matrix | calculate_clustering_metrics |
Calculate cluster entropy per class | class_entropy |
Calculate cluster purity per class | class_purity |
Generate a confusion matrix from two classifications/clustering solutions. | get_conf_mat |
Decompose soft (fuzzy, probabilistic) membership to hard binary matrix | get_hard |
Make a vector of class labels into a hard binary matrix | labels_to_matrix |
Calculate overall cluster entropy | overall_entropy |
Calculate overall cluster purity | overall_purity |
Calculate overall percentage agreement | percentage_agreement |