survxai
survxai: an R package for structure-agnostic explanations of survival models - Published in JOSS (2018)
Science Score: 93.0%
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Found 1 DOI reference(s) in JOSS metadata -
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Published in Journal of Open Source Software
Scientific Fields
Repository
Explanations for survival models
Basic Info
- Host: GitHub
- Owner: MI2DataLab
- License: gpl-2.0
- Language: R
- Default Branch: master
- Homepage: https://mi2datalab.github.io/survxai/
- Size: 7.14 MB
Statistics
- Stars: 15
- Watchers: 6
- Forks: 3
- Open Issues: 1
- Releases: 4
Metadata Files
README.md
diff
! Please note that the `survxai` package is not actively maintained.
+ Consider using the succeeding `survex` package.
survex is available at https://github.com/modeloriented/survex.
survxai
Survival analysis models are used primarily in medicine and churn analysis. Due to many applications, we are witnessing a fast development of a wide range of black-box survival models. Their lack of interpretability makes them unusable for analyzes that require an understanding of the model behavior.
An R package survxai is a tool for creating explanations of survival models. For both, complex and simple survival models. It also enables to compare them. Currently, four explanation methods are implemented. We can divide them into 2 groups: local and global.
The read more about the surxvai package see paper survxai: an R package for structure-agnostic explanations of survival models in The Journal of Open Source Software.
Install
devtools::install_github("MI2DataLab/survxai")
CheatSheet
News
Informations about changes in survxai relases can be found in NEWS.
How to contribute
Informations about creating issues and pull requests in survxai can be found in CONTRIBUTING.
Acknowledgments
Work on this package is financially supported by the 'NCN Opus grant 2016/21/B/ST6/02176'.
Owner
- Name: MI^2 DataLab
- Login: MI2DataLab
- Kind: organization
- Location: Warsaw, Poland
- Website: https://mi2.ai/
- Repositories: 49
- Profile: https://github.com/MI2DataLab
JOSS Publication
survxai: an R package for structure-agnostic explanations of survival models
Authors
Tags
survival analysis explainable artificial intelligence predictive modeling interpretable machine learningGitHub Events
Total
Last Year
Committers
Last synced: 7 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| Aleksandra Grudziąż | o****a@g****m | 69 |
| Alicja Gosiewska | a****a@g****m | 66 |
| Mateusz Staniak | m****t@m****l | 1 |
| Hubert Baniecki | h****i@g****m | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 26
- Total pull requests: 1
- Average time to close issues: 3 months
- Average time to close pull requests: about 2 hours
- Total issue authors: 8
- Total pull request authors: 1
- Average comments per issue: 0.77
- Average comments per pull request: 1.0
- Merged pull requests: 1
- 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
Top Authors
Issue Authors
- pbiecek (12)
- agosiewska (4)
- dirmeier (3)
- hiendn (2)
- AleksandraDabrowska (2)
- vasim07 (1)
- aalhadab (1)
- hbaniecki (1)
Pull Request Authors
- mstaniak (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
- Total downloads: unknown
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 2
conda-forge.org: r-survxai
- Homepage: https://mi2datalab.github.io/survxai/
- License: GPL
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Latest release: 0.2.2
published over 5 years ago
Rankings
Dependencies
- prodlim * depends
- breakDown * imports
- ggplot2 * imports
- pec * imports
- scales * imports
- survival * imports
- survminer * imports
- CFC * suggests
- DALEX * suggests
- covr * suggests
- knitr * suggests
- randomForestSRC * suggests
- rmarkdown * suggests
- rms * suggests
- testthat * suggests
- tibble * suggests
