Package: svrpath 0.1.2
svrpath: The SVR Path Algorithm
Computes the entire solution paths for Support Vector Regression(SVR) with respect to the regularization parameter, lambda and epsilon in epsilon-intensive loss function, efficiently. We call each path algorithm svrpath and epspath. See Wang, G. et al (2008) <doi:10.1109/TNN.2008.2002077> for details regarding the method.
Authors:
svrpath_0.1.2.tar.gz
svrpath_0.1.2.zip(r-4.5)svrpath_0.1.2.zip(r-4.4)svrpath_0.1.2.zip(r-4.3)
svrpath_0.1.2.tgz(r-4.4-any)svrpath_0.1.2.tgz(r-4.3-any)
svrpath_0.1.2.tar.gz(r-4.5-noble)svrpath_0.1.2.tar.gz(r-4.4-noble)
svrpath_0.1.2.tgz(r-4.4-emscripten)svrpath_0.1.2.tgz(r-4.3-emscripten)
svrpath.pdf |svrpath.html✨
svrpath/json (API)
| # Install 'svrpath' in R: |
| install.packages('svrpath', repos = c('https://09dohkim.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 6 years agofrom:9d32f1832a. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 14 2024 |
| R-4.5-win | OK | Sep 14 2024 |
| R-4.5-linux | OK | Sep 14 2024 |
| R-4.4-win | OK | Sep 14 2024 |
| R-4.4-mac | OK | Sep 14 2024 |
| R-4.3-win | OK | Sep 14 2024 |
| R-4.3-mac | OK | Sep 14 2024 |
Exports:epspathplot.epspathplot.svrpathpredict.epspathpredict.svrpathsolve.svrsvrpath
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Fit the entire 'epsilon' path for Support Vector Regression | epspath |
| plot the epspath, solution paths of SVR as a function of epsilon | plot.epspath |
| plot the svrpath, solution paths of SVR as a function of lambda | plot.svrpath |
| Make predictions from an "epspath" object | predict.epspath |
| Make predictions from a "svrpath" object | predict.svrpath |
| QP solver for SVR | solve.svr |
| Fit the entire regularization path for Support Vector Regression | svrpath |
