Shael Brown
2022-Aug-15 17:20 UTC
[R] [R-pkgs] TDApplied: Machine Learning and Inference for Topological Data Analysis
Dear R users, I am very excited to announce my new package TDApplied is now available on CRAN. Topological data analysis is a powerful tool for finding non-linear global structure in whole datasets. 'TDApplied' aims to bridge topological data analysis with data, statistical and machine learning practitioners so that more analyses may benefit from the power of topological data analysis. The main tool of topological data analysis is persistent homology, which computes a shape descriptor of a dataset, called a persistence diagram. There are three goals of this package: (1) convert persistence diagrams computed using the two main R packages for topological data analysis into a data frame, (2) implement fast versions of both distance and kernel calculations for pairs of persistence diagrams, and (3) provide scalable methods for machine learning and inference for persistence diagrams. For details and examples please check out the github page https://github.com/shaelebrown/TDApplied or the README file on CRAN https://cran.r-project.org/web/packages/TDApplied/readme/README.html I sincerely hope that you will enjoy using this package and that it helps the field of topological data analysis progress in both academia and industry. Best regards, Shael [[alternative HTML version deleted]] _______________________________________________ R-packages mailing list R-packages at r-project.org https://stat.ethz.ch/mailman/listinfo/r-packages