README.md

In wrathematics/ssvm: Simple SVM

ssvm

• Version: 0.1-0
• Status:
• License:
• Author: Drew Schmidt

ssvm is the Simple SVM package. It has a 2-class linear SVM implementation using the Pegasos algorithm, written on my day off for fun. The design philosophy for the project is:

1. Use a clean C backend to handle the heavy lifting.
2. The implementation is reasonably efficient. One could work a bit harder to make this faster, but I think all of the "easy" gains have already been achieved.
3. The R interface doesn't use formulas. Oh my god do not get me started on fucking formulas. If I could ban one thing from R, it would be formulas and I wouldn't even have to stop and think about it.
4. The secret ingredient is love.

Installation

The development version is maintained on GitHub, and can easily be installed by any of the packages that offer installations from GitHub:

### Pick your preference
devtools::install_github("wrathematics/ssvm")
ghit::install_github("wrathematics/ssvm")
remotes::install_github("wrathematics/ssvm")

Package Use

library(ssvm)

y <- recode(iris$Species == "setosa")
x <- as.matrix(iris[, -5])

set.seed(1234)
mdl <- pegasos(x, y)
mdl
## SVM model (Method=Pegasos, Iterations=1e+05)
##    Intercept Sepal.Length  Sepal.Width Petal.Length  Petal.Width 
##   -0.08139028  -0.12708726  -0.45953076   0.68090852   0.33553786  

mdl <- pegasos(x, y, intercept=FALSE)
mdl
## SVM model (Method=Pegasos, Iterations=1e+05)
## Sepal.Length  Sepal.Width Petal.Length  Petal.Width 
##   -0.1358138   -0.4659208    0.6824105    0.3382079 

p <- predict(mdl, x)
sum(which(p != y))
## 0

wrathematics/ssvm documentation built on May 4, 2019, 10:54 a.m.