Package: TDApplied
Type: Package
Title: Machine Learning and Inference for Topological Data Analysis
Version: 2.0.3
Authors@R: c(person("Shael", "Brown", email = "shaelebrown@gmail.com", role = c("aut","cre")),
             person("Dr. Reza", "Farivar", email = "reza.farivar@mcgill.ca", role = c("aut","fnd")))
Author: Shael Brown [aut, cre],
  Dr. Reza Farivar [aut, fnd]
Maintainer: Shael Brown <shaelebrown@gmail.com>
Description: 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 five goals of this package: (1) deliver a fast implementation
    of persistent homology via a python interface, (2) convert persistence diagrams
    computed using the two main R packages for topological data analysis into a data frame, 
    (3) implement fast versions of both distance and kernel calculations
    for pairs of persistence diagrams, (4) contribute tools for the interpretation of
    persistence diagrams, and (5) provide parallelized methods for machine learning
    and inference for persistence diagrams.
Depends: R (>= 3.2.2)
Imports: parallel, doParallel, foreach, clue, rdist, parallelly,
        kernlab, iterators, methods, stats, utils
License: GPL-3
URL: https://github.com/shaelebrown/TDApplied
BugReports: https://github.com/shaelebrown/TDApplied/issues
Encoding: UTF-8
NeedsCompilation: yes
RoxygenNote: 7.1.2
Suggests: rmarkdown, knitr, testthat (>= 3.0.0), TDA, TDAstats,
        reticulate
VignetteBuilder: knitr
Config/testthat/edition: 3
Packaged: 2023-01-15 15:01:39 UTC; jibaccount
Repository: CRAN
Date/Publication: 2023-01-15 19:00:06 UTC
