# plotLSVM: plot of LSVM In mistral: Methods in Structural Reliability Analysis

## Description

Make a plot of the data and the LSVM classifier

## Usage

 ```1 2 3 4 5 6``` ``` plotLSVM(X, Y, A.model.lsvm, hyperplanes = FALSE, limit.state.estimate = TRUE, 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. `A.model.lsvm` a matrix containing the parameters of all hyperplanes. `hyperplanes` A boolean. If TRUE, plot the hyperplanes obtained. `limit.state.estimate` A boolean. If TRUE, plot the estimate of the limit state. `convexity` Either -1 if the set of data associated to the label "-1" is convex or +1 otherwise.

## Details

plotLSVM makes a plot of the data as well as the estimate limit state and the hyperplanes involved in this construction.

## Note

This function is useful only in dimension 2.

## 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 .

`LSVM` `modelLSVM`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14``` ```# 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))}) ## Not run: model.A <- modelLSVM(X,Y, convexity = -1) plotLSVM(X, Y, model.A, hyperplanes = FALSE, limit.state.estimate = TRUE, convexity = -1) ## End(Not run) ```