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penalizedSVM (version 1.1.4)

Feature Selection SVM using Penalty Functions

Description

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.

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Version

Install

install.packages('penalizedSVM')

Monthly Downloads

255

Version

1.1.4

License

GPL (>= 2)

Maintainer

Frederic Bertrand

Last Published

March 23rd, 2023

Functions in penalizedSVM (1.1.4)

findgacv.scad

Calculate Generalized Approximate Cross Validation Error Estimation for SCAD SVM model
lpsvm

Fit L1-norm SVM
svmfs

Fits SVM with variable selection using penalties.
predict

Predict Method for Feature Selection SVM
print

Print Function for FS SVM
sim.data

Simulation of microarray data
scadsvc

Fit SCAD SVM model
penalizedSVM-package

Feature Selection SVM using Penalty Functions
penaltySVM-internal

Internal penaltySVM objects
.plot.EPSGO.parms

Plot Interval Search Plot Visited Points and the Q Values.
EPSGO

Fits SVM with variable selection using penalties.
sortmat

Sort matrix or data frame