Science Score: 33.0%
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○CITATION.cff file
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✓DOI references
Found 1 DOI reference(s) in README -
✓Academic publication links
Links to: ncbi.nlm.nih.gov -
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1 of 6 committers (16.7%) from academic institutions -
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○Scientific vocabulary similarity
Low similarity (10.6%) to scientific vocabulary
Repository
Fast Clustering Using Adaptive Density Peak Detection
Basic Info
- Host: GitHub
- Owner: ethanyxu
- Language: R
- Default Branch: master
- Homepage: http://hal.case.edu/~yifan/ADPclust.html
- Size: 1.98 MB
Statistics
- Stars: 10
- Watchers: 5
- Forks: 6
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
Introduction
ADPclust (Fast Clustering Using Adaptive Density Peak Detection) is a non-iterative procedure that clusters high dimensional data by finding cluster centers from estimated density peaks. It incorporates multivariate local Gaussian density estimation. The number of clusters as well as bandwidths can either be selected by the user or selected automatically through an internal clustering criterion.
Most recent version: 0.7
References
- Vignette: https://cran.r-project.org/web/packages/ADPclust/vignettes/ADPclust.html
- CRAN release (0.7): https://cran.r-project.org/web/packages/ADPclust/index.html
- Journal paper:
- Xiao-Feng Wang, and Yifan Xu, (2015) "Fast Clustering Using Adaptive Density Peak Detection." Statistical Methods in Medical Research, doi:10.1177/0962280215609948 (PubMed Link)
- Alex Rodriguez, and Alessandro Laio, (2014) "Clustering by fast search and find of density peaks." Science 344, no. 6191 (2014): 1492-1496
Installation
Install the most recent version from github: ```R
In R do:
Skip this line if you already have devtools installed
install.packages("devtools") library(devtools) install_github("ethanyxu/ADPclust") library(ADPclust) ```
OR install the released version from CRAN ```R
In R do:
install.packages("ADPclust") library(ADPclust) ```
Simple Examples
Run on a preloaded data set: ```R library(ADPclust) data(clust3)
Automatic clustering
ans <- adpclust(clust3) plot(ans) summary(ans)
Manual centroids selection
adpclust(clust3, centroids = "user") ``` For more examples please see the Vignette.
Owner
- Name: Yifan (Ethan) Xu
- Login: ethanyxu
- Kind: user
- Location: Seattle
- Company: Amazon.com
- Repositories: 5
- Profile: https://github.com/ethanyxu
Applied Scientist II
GitHub Events
Total
Last Year
Committers
Last synced: over 2 years ago
Top Committers
| Name | Commits | |
|---|---|---|
| Yifan (Ethan) Xu | e****u | 6 |
| Yifan (Ethan) Xu | e****u@u****m | 4 |
| Yifan (Ethan) Xu | e****u@e****l | 4 |
| Yifan (Ethan) Xu | e****u@g****m | 3 |
| Ethan Xu | x****a@a****m | 3 |
| Xiaofeng Wang | x****g@g****m | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 11 months ago
All Time
- Total issues: 0
- Total pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Total issue authors: 0
- Total pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
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Packages
- Total packages: 1
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Total downloads:
- cran 234 last-month
- Total docker downloads: 43,390
- Total dependent packages: 1
- Total dependent repositories: 1
- Total versions: 3
- Total maintainers: 1
cran.r-project.org: ADPclust
Fast Clustering Using Adaptive Density Peak Detection
- Homepage: https://github.com/ethanyxu/ADPclust
- Documentation: http://cran.r-project.org/web/packages/ADPclust/ADPclust.pdf
- License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
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Latest release: 0.6.5
published over 10 years ago
Rankings
Maintainers (1)
Dependencies
- R >= 4.0.0 depends
- cluster * imports
- dplyr * imports
- fields * imports
- knitr * imports
- rmarkdown * suggests
- testthat * suggests