CRAN/E | TDApplied

TDApplied

Machine Learning and Inference for Topological Data Analysis

Installation

About

Topological data analysis is a powerful tool for finding non-linear global structure in whole datasets. The main tool of topological data analysis is persistent homology, which computes a topological shape descriptor of a dataset called a persistence diagram. 'TDApplied' provides useful and efficient methods for analyzing groups of persistence diagrams with machine learning and statistical inference, and these functions can also interface with other data science packages to form flexible and integrated topological data analysis pipelines.

github.com/shaelebrown/TDApplied
Bug report File report

Key Metrics

Version 3.0.3
R ≥ 3.5.0
Published 2024-03-12 16 days ago
Needs compilation? yes
License GPL (≥ 3)
CRAN checks TDApplied results

Downloads

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Maintainer

Maintainer

Shael Brown

shaelebrown@gmail.com

Authors

Shael Brown

aut / cre

Dr. Reza Farivar

aut / fnd

Material

README
NEWS
Reference manual
Package source

Vignettes

Human Connectome Project Analysis
TDApplied Theory and Practice
Benchmarking and Speedups
Comparing Distance Calculations
Personalized Analyses with TDApplied

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

TDApplied archive

Depends

R ≥ 3.5.0

Imports

parallel
doParallel
foreach
clue
rdist
parallelly
kernlab
iterators
methods
stats
utils
Rcpp ≥ 0.11.0

Suggests

rmarkdown
knitr
testthat ≥ 3.0.0
TDAstats
reticulate
igraph

LinkingTo

Rcpp