rocsvm.solve {rocsvm.path}

Finding Lagrangian multipliers of ROC-SVM by Qudratic Programming

Description

Computes the Lagrangian multipliers(alpha), which are solutions of ROC-SVM using Quadratic Programming.

Usage

rocsvm.solve(K, lambda, rho = 1, eps = 1e-08)

Arguments

K

The kernelized matrix, i.e., K< .,. >.

lambda

The regularization parameter that users want in ROC-SVM model.

rho

A positive constant (default : 1)

eps

Adjustment computing errors (default : 1e-08)

Author(s)

Seung Jun Shin, Do Hyun Kim

See Also

rocsvm.path

Examples

n <- 30
p <- 2
delta <- 1
set.seed(309)
y <- c(rep(1, n/2), rep(-1, n/2))
x <- matrix(0, n, p)
for (i in 1:n){
 if (y[i] == 1) {
 x[i,] <- rnorm(p, -delta, 1)
 } else {
 x[i,] <- rnorm(p, delta, 1)
  }
 }

K <- radial.kernel(x,x)
rocsvm.solve(K, lambda = 1, rho = 1)