modelLSVM: Estimation of the parameters of the LSVM

In clemlaflemme/test: Methods in Structural Reliability

Description

Produce a matrix containing the parameters of a set of hyperplanes separating the two classes of data

Usage

  modelLSVM(X, Y, convexity)

Arguments

X	a matrix containing the data sets
Y	a vector containing -1 or +1 that reprensents the class of each elements of X.
convexity	Either -1 if the set of data associated to the label "-1" is convex or +1 otherwise.

Details

modelLSVM evaluate the classifier on a set of points.

Value

An object of class matrix containing the parameters of a set of hyperplanes

res	A matrix where each lines contains the parameters of a hyperplane.

Author(s)

Vincent Moutoussamy

References

• R.T. Rockafellar:
  Convex analysis
  Princeton university press, 2015.
  

• N. Bousquet, T. Klein and V. Moutoussamy :
  Approximation of limit state surfaces in monotonic Monte Carlo settings
  Submitted .
  

See Also

LSVM

Examples

# A limit state function
f <- function(x){  sqrt(sum(x^2)) - sqrt(2)/2 }

# Creation of the data sets
n <- 200
X <- matrix(runif(2*n), nrow = n)
Y <- apply(X, MARGIN = 1, function(w){sign(f(w))})

#The convexity is known
## Not run: 
  model.A <- modelLSVM(X, Y, convexity = -1)

## End(Not run)

clemlaflemme/test documentation built on Jan. 3, 2020, 9:14 a.m.