mistral (version 2.1.0)

modelLSVM: Estimation of the parameters of the LSVM

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.

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.

Details

modelLSVM evaluate the classifier on a set of points.

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

# NOT RUN {
# 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)
# }
# NOT RUN {
# }