Notation | Similarity Measures | Cosine similarity ("cosine") | Pearson correlation coefficient ("correlation") | Jaccard similarity ("jaccard" and "ejaccard") | Fuzzy Jaccard similarity ("fjaccard") | Dice similarity ("dice" and "edice") | Hamann similarity ("hamann") | Faith similarity ("faith") | Simple matching ("matching") | Distance Measures | Manhattan distance ("manhattan") | Canberra distance ("canberra") | Euclidian ("euclidian") | Minkowski distance ("minkowski") | Hamming distance ("hamming") | The largest difference between values ("maximum") | Chi-squared divergence ("chisquared") | Kullback--Leibler divergence ("kullback") | Jeffreys divergence ("jeffreys") | Jensen-Shannon divergence ("jensen") | References
This package is considered a duplicate. The official version of this package is found at:https://koheiw.r-universe.dev/proxyC
Package: proxyC 0.6.0
Kohei Watanabe
proxyC: Computes Proximity in Large Matrices
Computes proximity between rows or columns of large matrices efficiently in C++. Functions are optimised for large matrices using the Armadillo and Intel TBB libraries. Among various built-in similarity/distance measures, computation of correlation, cosine similarity, Dice coefficient and Euclidean distance is particularly fast.
Authors:
proxyC_0.6.0.tar.gz
proxyC_0.6.0.zip(r-4.7-x86_64)proxyC_0.6.0.zip(r-4.7-arm64)proxyC_0.6.0.zip(r-4.6-x86_64)proxyC_0.6.0.zip(r-4.6-arm64)
proxyC_0.6.0.tar.gz(r-4.7-arm64)proxyC_0.6.0.tar.gz(r-4.7-x86_64)proxyC_0.6.0.tar.gz(r-4.6-arm64)proxyC_0.6.0.tar.gz(r-4.6-x86_64)
proxyC_0.6.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
proxyC/json (API)
| # Install 'proxyC' in R: |
| install.packages('proxyC', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/koheiw/proxyc/issues
Pkgdown/docs site:https://koheiw.github.io
Uses libs:
Last updated from:9550c4c4b5. Checks:10 OK. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 161 | ||
| linux-devel-x86_64 | OK | 169 | ||
| source / vignettes | OK | 227 | ||
| linux-release-arm64 | OK | 161 | ||
| linux-release-x86_64 | OK | 180 | ||
| windows-devel-arm64 | OK | 247 | ||
| windows-devel-x86_64 | OK | 225 | ||
| windows-release-arm64 | OK | 286 | ||
| windows-release-x86_64 | OK | 198 | ||
| wasm-release | OK | 123 |
Exports:colMaxscolMinscolSdscolZeroscrossproddistmaskmaxColmaxRowrowMaxsrowMinsrowSdsrowZerossimiltcrossprod
Dependencies:latticeMatrixRcppRcppArmadillo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Maximum/minimum values in columns or rows | colMaxs colMins rowMaxs rowMins |
| Standard deviation of columns and rows of large matrices | colSds rowSds |
| Number of zeros in columns and rows of large matrices | colZeros rowZeros |
| Cross-product of large sparse matrices | crossprod tcrossprod |
| Create a pattern matrix for masking | mask |
| Column or row indices of maximum values | maxCol maxRow |
| Compute similarity/distance between rows or columns of large matrices | dist simil |