n = 2;
randn('state',2);
N = 50; M = 50;
Y = [1.5+0.9*randn(1,0.6*N), 1.5+0.7*randn(1,0.4*N);
2*(randn(1,0.6*N)+1), 2*(randn(1,0.4*N)-1)];
X = [-1.5+0.9*randn(1,0.6*M), -1.5+0.7*randn(1,0.4*M);
2*(randn(1,0.6*M)-1), 2*(randn(1,0.4*M)+1)];
T = [-1 1; 1 1];
Y = T*Y; X = T*X;
cvx_begin
variables a(n) b(1) u(N) v(M)
minimize (ones(1,N)*u + ones(1,M)*v)
X'*a - b >= 1 - u;
Y'*a - b <= -(1 - v);
u >= 0;
v >= 0;
cvx_end
linewidth = 0.5;
t_min = min([X(1,:),Y(1,:)]);
t_max = max([X(1,:),Y(1,:)]);
tt = linspace(t_min-1,t_max+1,100);
p = -a(1)*tt/a(2) + b/a(2);
p1 = -a(1)*tt/a(2) + (b+1)/a(2);
p2 = -a(1)*tt/a(2) + (b-1)/a(2);
graph = plot(X(1,:),X(2,:), 'o', Y(1,:), Y(2,:), 'o');
set(graph(1),'LineWidth',linewidth);
set(graph(2),'LineWidth',linewidth);
set(graph(2),'MarkerFaceColor',[0 0.5 0]);
hold on;
plot(tt,p, '-r', tt,p1, '--r', tt,p2, '--r');
axis equal
title('Approximate linear discrimination via linear programming');
Calling SDPT3 4.0: 203 variables, 100 equality constraints
------------------------------------------------------------
num. of constraints = 100
dim. of linear var = 200
dim. of free var = 3 *** convert ublk to lblk
*******************************************************************
SDPT3: Infeasible path-following algorithms
*******************************************************************
version predcorr gam expon scale_data
NT 1 0.000 1 0
it pstep dstep pinfeas dinfeas gap prim-obj dual-obj cputime
-------------------------------------------------------------------
0|0.000|0.000|9.1e-01|1.9e+01|4.1e+04| 1.414214e+03 0.000000e+00| 0:0:00| chol 1 1
1|1.000|0.968|1.2e-06|7.1e-01|2.6e+03| 1.241114e+03 1.166168e+01| 0:0:00| chol 1 1
2|1.000|0.567|2.7e-06|3.1e-01|1.0e+03| 4.476059e+02 8.828967e+00| 0:0:00| chol 1 1
3|0.910|0.846|1.6e-06|4.9e-02|1.4e+02| 6.788544e+01 6.105312e+00| 0:0:00| chol 1 1
4|0.940|0.640|6.2e-06|1.8e-02|6.3e+01| 3.280721e+01 4.752207e+00| 0:0:00| chol 1 1
5|0.982|0.439|6.7e-07|1.0e-02|2.8e+01| 1.368275e+01 4.223464e+00| 0:0:00| chol 1 1
6|1.000|0.754|7.9e-09|2.5e-03|1.1e+01| 1.107127e+01 4.125359e+00| 0:0:00| chol 1 1
7|1.000|0.241|5.0e-08|1.9e-03|8.2e+00| 9.815542e+00 4.091411e+00| 0:0:00| chol 1 1
8|1.000|0.587|1.5e-07|7.7e-04|5.0e+00| 8.915113e+00 4.980641e+00| 0:0:00| chol 1 1
9|0.921|0.455|8.2e-08|4.2e-04|2.4e+00| 7.197481e+00 5.289285e+00| 0:0:00| chol 1 1
10|1.000|0.524|2.6e-08|2.0e-04|1.4e+00| 6.805736e+00 5.594202e+00| 0:0:00| chol 1 1
11|1.000|0.299|1.3e-08|1.4e-04|1.0e+00| 6.562960e+00 5.719608e+00| 0:0:00| chol 1 1
12|1.000|0.516|6.2e-09|6.8e-05|6.2e-01| 6.439207e+00 5.882265e+00| 0:0:00| chol 1 1
13|0.755|0.303|2.4e-09|4.7e-05|4.0e-01| 6.292514e+00 5.919046e+00| 0:0:00| chol 1 1
14|1.000|0.303|3.4e-10|3.3e-05|4.1e-01| 6.372321e+00 5.996721e+00| 0:0:00| chol 1 1
15|0.983|0.306|2.6e-10|2.3e-05|2.4e-01| 6.245623e+00 6.016152e+00| 0:0:00| chol 1 1
16|1.000|0.679|1.3e-09|7.3e-06|7.8e-02| 6.169151e+00 6.095341e+00| 0:0:00| chol 1 1
17|0.993|0.899|5.9e-11|7.4e-07|6.7e-03| 6.149220e+00 6.142910e+00| 0:0:00| chol 1 1
18|0.987|0.986|2.5e-10|3.1e-06|1.4e-04| 6.148578e+00 6.148492e+00| 0:0:00| chol 1 1
19|0.996|0.989|1.1e-12|6.5e-08|3.5e-06| 6.148570e+00 6.148568e+00| 0:0:00| chol 1 1
20|1.000|0.989|7.9e-14|1.6e-09|7.9e-08| 6.148569e+00 6.148569e+00| 0:0:00|
stop: max(relative gap, infeasibilities) < 1.49e-08
-------------------------------------------------------------------
number of iterations = 20
primal objective value = 6.14856945e+00
dual objective value = 6.14856940e+00
gap := trace(XZ) = 7.91e-08
relative gap = 5.95e-09
actual relative gap = 4.14e-09
rel. primal infeas (scaled problem) = 7.87e-14
rel. dual " " " = 1.60e-09
rel. primal infeas (unscaled problem) = 0.00e+00
rel. dual " " " = 0.00e+00
norm(X), norm(y), norm(Z) = 8.9e+01, 2.4e+00, 1.0e+01
norm(A), norm(b), norm(C) = 7.3e+01, 1.1e+01, 1.1e+01
Total CPU time (secs) = 0.21
CPU time per iteration = 0.01
termination code = 0
DIMACS: 4.3e-13 0.0e+00 8.8e-09 0.0e+00 4.1e-09 6.0e-09
-------------------------------------------------------------------
------------------------------------------------------------
Status: Solved
Optimal value (cvx_optval): +6.14857