Package: penalizedSVM 1.2.0
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_1.2.0.tar.gz
penalizedSVM_1.2.0.zip(r-4.7)penalizedSVM_1.2.0.zip(r-4.6)penalizedSVM_1.2.0.zip(r-4.5)
penalizedSVM_1.2.0.tgz(r-4.6-any)penalizedSVM_1.2.0.tgz(r-4.5-any)
penalizedSVM_1.2.0.tar.gz(r-4.7-any)penalizedSVM_1.2.0.tar.gz(r-4.6-any)
penalizedSVM_1.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
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
Pkgdown/docs site:https://fbertran.github.io
Last updated from:333e55010f. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 112 | ||
| source / vignettes | OK | 194 | ||
| linux-release-x86_64 | OK | 113 | ||
| macos-release-arm64 | OK | 71 | ||
| macos-oldrel-arm64 | OK | 115 | ||
| windows-devel | OK | 95 | ||
| windows-release | OK | 69 | ||
| windows-oldrel | OK | 70 | ||
| wasm-release | OK | 91 |
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 |
