**** Create some sample data *******; 
data percept; 
  do example = 1 to 20; 
    X1 = ranuni(1827655); X2=ranuni(1827655); 
    Y = 1 - X1 - X2; YY = -1 + 2*(Y>0); 
    Radius = sqrt(x1*x1+x2*x2); 
output; end; 
proc print; 


***** Compute sample radius *****************; 
proc means max; var radius; output out=R max=R; 



***** Rosenblatt perceptron ***************; 
proc iml; 
use percept; read all var{x1 X2} into X; 
            read all var{Y} into Y; 
            read all var{YY} into YY; 
use R; read all var {R} into R; RR=R*R; RR=1.355254;
print X Y YY R RR; 

W={0,0}; b=0; k=0; L=nrow(X); eta=.8; 
print w b k L eta; 

do step = 1 to 6;    *** <--- stop after 6 steps max ***; 
mistakes=0; 
do i=1 to L; 
     if Y[i, ]*(X[i, ]*W + b) <= 0 then do; 
       W = W + eta*Y[i, ]*X[i, ]`; 
       b = b + eta*Y[i, ]*RR; 
       k=k+1; mistakes=mistakes+1; 
     end; 
end; 
print W b k mistakes;  
end; 

print "Final values" W b; 


*** Assemble data then output to data set gdat ****; 
data = shape(0,20,4); 
do i = 1 to 20; 
  data[i,1] = i/20; 
  data[i,2] = -( b + W[1,1]*data[i,1])/W[2,1]; 
  data[i,3:4] = {. 2}; 
end; 
print data; 

out = (X||y||YY)//data; 
print out; 

create gdat from out; 
append from out; 


*** Using gdat data, graph data and splitter ***; 
proc gplot data=gdat; 
plot col1*col2 = col4; 
symbol1 v=dot c=red; 
symbol2 v=dot c=green;
symbol3 v=none i=join c=black; 
run; quit;