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edarf

edarf: Exploratory Data Analysis using Random Forests - Published in JOSS (2016)

https://github.com/zmjones/edarf

Science Score: 49.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 4 DOI reference(s) in README
  • ✓
    Academic publication links
    Links to: joss.theoj.org, zenodo.org
  • ○
    Committers with academic emails
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    Institutional organization owner
  • ○
    JOSS paper metadata
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    Scientific vocabulary similarity
    Low similarity (12.0%) to scientific vocabulary

Keywords

exploratory-data-analysis machine-learning r random-forest rstats
Last synced: 6 months ago · JSON representation

Repository

exploratory data analysis using random forests

Basic Info
  • Host: GitHub
  • Owner: zmjones
  • License: mit
  • Language: R
  • Default Branch: master
  • Size: 6.92 MB
Statistics
  • Stars: 68
  • Watchers: 13
  • Forks: 11
  • Open Issues: 2
  • Releases: 1
Topics
exploratory-data-analysis machine-learning r random-forest rstats
Created over 11 years ago · Last pushed about 8 years ago
Metadata Files
Readme License

README.md

DOI status

Functions useful for exploratory data analysis using random forests.

This package extends the functionality of random forests fit by party (multivariate, regression, and classification), randomForestSRC (regression and classification,), randomForest (regression and classification), and ranger (classification and regression).

The subdirectory pkg contains the actual package. The package can be installed with devtools.

{r} devtools::install_github("zmjones/edarf", subdir = "pkg")

Functionality includes:

  • partial_dependence which computes the expected prediction made by the random forest if it were marginalized to only depend on a subset of the features. plot_pd plots the results.
  • variable_importance which computes feature importance for arbitrary loss functions, aggregated across the training data or for individual observations. This may also be used for subsets of the feature space in order to detect interactions.
  • extract_proximity and plot_prox which computes or extracts proximity matrices and plots them using a biplot given a matrix of principal components of said matrix.

If you use the package for research, please cite it.

@article{jones2016,
  doi = {10.21105/joss.00092},
  url = {http://dx.doi.org/10.21105/joss.00092},
  year  = {2016},
  month = {oct},
  publisher = {The Open Journal},
  volume = {1},
  number = {6},
  author = {Zachary M. Jones and Fridolin J. Linder},
  title = {edarf: Exploratory Data Analysis using Random Forests},
  journal = {The Journal of Open Source Software}
}

Pull requests, bug reports, feature requests, etc. are welcome!

Owner

  • Name: Zachary Jones
  • Login: zmjones
  • Kind: user
  • Company: Meta

GitHub Events

Total
Last Year

Committers

Last synced: 7 months ago

All Time
  • Total Commits: 286
  • Total Committers: 4
  • Avg Commits per committer: 71.5
  • Development Distribution Score (DDS): 0.091
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Zachary M. Jones z****j@z****m 260
flinder f****r@g****m 23
Christopher Gandrud c****d@g****m 2
Arfon Smith a****n 1
Committer Domains (Top 20 + Academic)
zmjones.com: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 50
  • Total pull requests: 7
  • Average time to close issues: 2 months
  • Average time to close pull requests: 27 days
  • Total issue authors: 11
  • Total pull request authors: 4
  • Average comments per issue: 2.12
  • Average comments per pull request: 2.57
  • Merged pull requests: 5
  • 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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Top Authors
Issue Authors
  • zmjones (30)
  • PhilippPro (7)
  • flinder (5)
  • stefanherzog (1)
  • mikajoh (1)
  • nakamichiworks (1)
  • danilofreire (1)
  • cjvanlissa (1)
  • HugoMH (1)
  • gavin-s-smith (1)
  • brooksandrew (1)
Pull Request Authors
  • christophergandrud (2)
  • zmjones (2)
  • reuning (2)
  • arfon (1)
Top Labels
Issue Labels
enhancement (7) bug (4)
Pull Request Labels

Dependencies

pkg/DESCRIPTION cran
  • R >= 2.10 depends
  • data.table * imports
  • ggplot2 * imports
  • mmpf * imports
  • knitr * suggests
  • party * suggests
  • randomForest * suggests
  • randomForestSRC * suggests
  • ranger * suggests
  • rmarkdown * suggests
  • testthat * suggests