Package: proxyC 0.4.2

proxyC: Computes Proximity in Large Sparse Matrices

Computes proximity between rows or columns of large matrices efficiently in C++. Functions are optimised for large sparse matrices using the Armadillo and Intel TBB libraries. Among various built-in similarity/distance measures, computation of correlation, cosine similarity and Euclidean distance is particularly fast.

Authors:Kohei Watanabe [cre, aut, cph], Robrecht Cannoodt [aut]

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proxyC.pdf |proxyC.html✨
proxyC/json (API)
NEWS

# Install 'proxyC' in R:
install.packages('proxyC', repos = c('https://koheiw.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/koheiw/proxyc/issues

Uses libs:
  • openblas– Optimized BLAS
  • onetbb– Parallelism library for C++
  • c++– GNU Standard C++ Library v3

On CRAN:

data-sciencedistance-measuressimilarity-measures

8.96 score 29 stars 29 packages 23 scripts 5.3k downloads 6 exports 4 dependencies

Last updated 13 days agofrom:747f57d32b. Checks:OK: 7 NOTE: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 24 2024
R-4.5-win-x86_64NOTEOct 24 2024
R-4.5-linux-x86_64NOTEOct 24 2024
R-4.4-win-x86_64OKOct 24 2024
R-4.4-mac-x86_64OKOct 24 2024
R-4.4-mac-aarch64OKOct 24 2024
R-4.3-win-x86_64OKOct 24 2024
R-4.3-mac-x86_64OKOct 24 2024
R-4.3-mac-aarch64OKOct 24 2024

Exports:colSdscolZerosdistrowSdsrowZerossimil

Dependencies:latticeMatrixRcppRcppArmadillo

Similarity and Distance Measures in proxyC

Kohei Watanabe

Rendered frommeasures.Rmdusingknitr::rmarkdownon Oct 24 2024.

Last update: 2024-10-15
Started: 2022-10-05