ipop-class: Class "ipop"

In elad663/kernlab: Kernel-Based Machine Learning Lab

Description

The quadratic problem solver class

Objects from the Class

Objects can be created by calls of the form new("ipop", ...). or by calling the ipop function.

Slots

primal:

Object of class "vector" the primal solution of the problem

dual:

Object of class "numeric" the dual of the problem

how:

Object of class "character" convergence information

Methods

primal

Object of class ipop

Return the primal of the problem

dual

Object of class ipop

Return the dual of the problem

how

Object of class ipop

Return information on convergence

Author(s)

Alexandros Karatzoglou
[e-mail]

See Also

ipop

Examples

## solve the Support Vector Machine optimization problem
data(spam)

## sample a scaled part (300 points) of the spam data set
m <- 300
set <- sample(1:dim(spam)[1],m)
x <- scale(as.matrix(spam[,-58]))[set,]
y <- as.integer(spam[set,58])
y[y==2] <- -1

##set C parameter and kernel
C <- 5
rbf <- rbfdot(sigma = 0.1)

## create H matrix etc.
H <- kernelPol(rbf,x,,y)
c <- matrix(rep(-1,m))
A <- t(y)
b <- 0
l <- matrix(rep(0,m))
u <- matrix(rep(C,m))
r <- 0

sv <- ipop(c,H,A,b,l,u,r)
primal(sv)
dual(sv)
how(sv)

elad663/kernlab documentation built on May 7, 2019, 6:06 a.m.