Package: FWDselect 2.1.0.9000
FWDselect: Selecting Variables in Regression Models
A simple method to select the best model or best subset of variables using different types of data (binary, Gaussian or Poisson) and applying it in different contexts (parametric or non-parametric).
Authors:
FWDselect_2.1.0.9000.tar.gz
FWDselect_2.1.0.9000.zip(r-4.5)FWDselect_2.1.0.9000.zip(r-4.4)FWDselect_2.1.0.9000.zip(r-4.3)
FWDselect_2.1.0.9000.tgz(r-4.4-any)FWDselect_2.1.0.9000.tgz(r-4.3-any)
FWDselect_2.1.0.9000.tar.gz(r-4.5-noble)FWDselect_2.1.0.9000.tar.gz(r-4.4-noble)
FWDselect_2.1.0.9000.tgz(r-4.4-emscripten)FWDselect_2.1.0.9000.tgz(r-4.3-emscripten)
FWDselect.pdf |FWDselect.html✨
FWDselect/json (API)
NEWS
| # Install 'FWDselect' in R: |
| install.packages('FWDselect', repos = c('https://sestelo.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/sestelo/fwdselect/issues
feature-engineeringfeature-selectionmachine-learning-algorithmsnonparametricregresssionvariable-importancevariable-selection
Last updated 9 years agofrom:1446635b14. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 20 2024 |
| R-4.5-win | OK | Nov 20 2024 |
| R-4.5-linux | OK | Nov 20 2024 |
| R-4.4-win | OK | Nov 20 2024 |
| R-4.4-mac | OK | Nov 20 2024 |
| R-4.3-win | OK | Nov 20 2024 |
| R-4.3-mac | OK | Nov 20 2024 |
Exports:qselectionselectiontest
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Diabetes data. | diabetes |
| Episode of SO2. Pollution incident data. | episode |
| 'FWDselect': Selecting Variables in Regression Models. | FWDselect-package FWDselect |
| Visualization of 'qselection' object | plot.qselection |
| Emission of SO2. Pollution incident data. | pollution |
| Short 'qselection' summary | print.qselection |
| Short 'selection' summary | print.selection |
| Selecting variables for several subset sizes | qselection |
| Selecting a subset of 'q' variables | selection |
| Bootstrap based test for covariate selection | test |
