Package: penalizedSVM 1.1.4
penalizedSVM: Feature Selection SVM using Penalty Functions
Support Vector Machine (SVM) classification with simultaneous feature selection using penalty functions is implemented. The smoothly clipped absolute deviation (SCAD), 'L1-norm', 'Elastic Net' ('L1-norm' and 'L2-norm') and 'Elastic SCAD' (SCAD and 'L2-norm') penalties are available. The tuning parameters can be found using either a fixed grid or a interval search.
Authors:
penalizedSVM_1.1.4.tar.gz
penalizedSVM_1.1.4.zip(r-4.5)penalizedSVM_1.1.4.zip(r-4.4)penalizedSVM_1.1.4.zip(r-4.3)
penalizedSVM_1.1.4.tgz(r-4.4-any)penalizedSVM_1.1.4.tgz(r-4.3-any)
penalizedSVM_1.1.4.tar.gz(r-4.5-noble)penalizedSVM_1.1.4.tar.gz(r-4.4-noble)
penalizedSVM_1.1.4.tgz(r-4.4-emscripten)penalizedSVM_1.1.4.tgz(r-4.3-emscripten)
penalizedSVM.pdf |penalizedSVM.html✨
penalizedSVM/json (API)
NEWS
| # Install 'penalizedSVM' in R: |
| install.packages('penalizedSVM', repos = c('https://fbertran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/fbertran/penalizedsvm/issues
Last updated 2 years agofrom:a9b3058db4. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 22 2024 |
| R-4.5-win | OK | Nov 22 2024 |
| R-4.5-linux | OK | Nov 22 2024 |
| R-4.4-win | OK | Nov 22 2024 |
| R-4.4-mac | OK | Nov 22 2024 |
| R-4.3-win | OK | Nov 22 2024 |
| R-4.3-mac | OK | Nov 22 2024 |
Exports:.plot.EPSGO.parmsDirectDrHSVMEPSGOExpImprovementfindgacv.scadlpsvmpredict.penSVMprint.penSVMscad_L2.svcscadsvcsim.datasortmatsvmfssvmfs.default
Dependencies:classclustercorpcore1071maptreeMASSmlegpproxyrpartstatmodtgp
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Feature Selection SVM using Penalty Functions | penalizedSVM-package penalizedSVM |
| Plot Interval Search Plot Visited Points and the Q Values. | .plot.EPSGO.parms |
| Fits SVM with variable selection using penalties. | Direct EPSGO ExpImprovement |
| Calculate Generalized Approximate Cross Validation Error Estimation for SCAD SVM model | findgacv.scad |
| Fit L1-norm SVM | lpsvm |
| Predict Method for Feature Selection SVM | predict.penSVM |
| Print Function for FS SVM | print.penSVM |
| Fit SCAD SVM model | scadsvc |
| Simulation of microarray data | sim.data |
| Sort matrix or data frame | sortmat |
| Fits SVM with variable selection using penalties. | DrHSVM scad_L2.svc svmfs svmfs.default |
