| Library: | xclust |
| See also: | svm adaptive divisive cartsplit cartcv |
| Quantlet: | svmplot | |
| Description: | support quantlet providing graphical output for svm.xpl. |
| Usage: | svmplot(AT,AC,V) | |
| Input: | ||
| AT | (m x d+1) matrix, contains d characteristics of m objects of the training set. The last column of the matrix must describe the class of an object, it can only be +1 or -1. Pararmeter AC | |
| V | (mm x d) matrix, contains d characteristics of mm objects whose classes (+1 or -1) are to be found. | |
| n/a | (mm x 1) vector, scores, ouput from svm.xpl. | |
library("xplore");
library("plot");
library("xclust");
AT=read("bankruptcy.dat");
nsteps=100;
origin=#(-0.62, 0.0);
endpoints=#(0.52, 1.5);
steps=(endpoints-origin)/nsteps;
npoints=#(nsteps+1, nsteps+1);
AC=grid(origin,steps,npoints);
V=svm(AT, AC, 2.0, 1.0);
; Try out these values of r and c: ;
; -------------------------------- ;
; r=100 ; c=1 ;
; r=2 ; c=1 ;
; r=0.5 ; c=1 ;
; ------------- ;
; r=2 ; c=300 ;
svmplot(AT,AC,V);
setgopt(svmdi,1,1,"xlabel","Profitability(NI/TA)","ylabel","Leverage(TL/TA)","title","Company Scores");
A two dimensional plot. Intensity of the background colour corresponds to the empirically estimated probability of default: the darker the area, the higher the company default probabilty.