modelLSVM {mistral} | R Documentation |
Produce a matrix containing the parameters of a set of hyperplanes separating the two classes of data
modelLSVM(X, Y, convexity)
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. |
modelLSVM evaluate the classifier on a set of points.
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. |
Vincent Moutoussamy
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 .
# 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)