Package: N2R 1.0.5
Evan Biederstedt
N2R: Fast and Scalable Approximate k-Nearest Neighbor Search Methods using 'N2' Library
Implements methods to perform fast approximate K-nearest neighbor search on input matrix. Algorithm based on the 'N2' implementation of an approximate nearest neighbor search using hierarchical Navigable Small World (NSW) graphs. The original algorithm is described in "Efficient and Robust Approximate Nearest Neighbor Search Using Hierarchical Navigable Small World Graphs", Y. Malkov and D. Yashunin, <doi:10.1109/TPAMI.2018.2889473>, <doi:10.48550/arXiv.1603.09320>.
Authors:
N2R_1.0.5.tar.gz
N2R_1.0.5.zip(r-4.7-x86_64)N2R_1.0.5.zip(r-4.7-arm64)N2R_1.0.5.zip(r-4.6-x86_64)N2R_1.0.5.zip(r-4.6-arm64)N2R_1.0.5.zip(r-4.5-x86_64)
N2R_1.0.5.tgz(r-4.6-x86_64)N2R_1.0.5.tgz(r-4.6-arm64)N2R_1.0.5.tgz(r-4.5-x86_64)N2R_1.0.5.tgz(r-4.5-arm64)
N2R_1.0.5.tar.gz(r-4.7-arm64)N2R_1.0.5.tar.gz(r-4.7-x86_64)N2R_1.0.5.tar.gz(r-4.6-arm64)N2R_1.0.5.tar.gz(r-4.6-x86_64)
N2R_1.0.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
N2R/json (API)
| # Install 'N2R' in R: |
| install.packages('N2R', repos = c('https://kharchenkolab.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/kharchenkolab/n2r/issues
Last updated from:8045c294d3. Checks:15 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 132 | ||
| linux-devel-x86_64 | OK | 134 | ||
| source / vignettes | OK | 184 | ||
| linux-release-arm64 | OK | 126 | ||
| linux-release-x86_64 | OK | 149 | ||
| macos-release-arm64 | OK | 142 | ||
| macos-release-x86_64 | OK | 330 | ||
| macos-oldrel-arm64 | OK | 109 | ||
| macos-oldrel-x86_64 | OK | 272 | ||
| windows-devel-arm64 | OK | 234 | ||
| windows-devel-x86_64 | OK | 194 | ||
| windows-release-arm64 | OK | 242 | ||
| windows-release-x86_64 | OK | 163 | ||
| windows-oldrel-x86_64 | OK | 154 | ||
| wasm-release | OK | 139 |
