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:Natalia Becker [aut], Wiebke Werft [aut], Axel Benner [aut], Frederic Bertrand [cre]

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✨
DESCRIPTION |NEWS
card.svg |card.png
penalizedSVM/json (API)

# 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

On CRAN:

4.45 score 1 stars 2 packages 94 scripts 700 downloads 1 mentions 15 exports 11 dependencies

Last updated from:333e55010f. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	93
source / vignettes	OK	155
linux-release-x86_64	OK	110
macos-release-arm64	OK	76
macos-oldrel-arm64	OK	88
windows-devel	OK	71
windows-release	OK	87
windows-oldrel	OK	71
wasm-release	OK	97

Exports:.plot.EPSGO.parms Direct DrHSVM EPSGO ExpImprovement findgacv.scad lpsvm predict.penSVM print.penSVM scad_L2.svc scadsvc sim.data sortmat svmfs svmfs.default

Dependencies:class cluster corpcor e1071 maptree MASS mlegp proxy rpart statmod tgp

Citation

Development and contributors

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