Introduction to Pattern Recognition: A Matlab Approach

194 CHAPTER 7 Clustering

x_coord=10;

for y=mini:step:maxi

X8=[X8; x_coord+noise*(rand-.5) y+noise*(rand-.5)];

end

To generate the third group, type

%Construction of the 3rd cluster (semicircle, center (21,0), R=3;, y<0)

R=3;

x_center=21;

y_center=0;

mini=x_center-R;

maxi=x_center+R;

step=(maxi-mini)/(n_points(3)-1);

for x=mini:step:maxi

y=y_center - sqrt(Rˆ2-(x-x_center)ˆ2)+noise*(rand-.5);

X8=[X8; x y];

end

Finally, to generate the fourth group, type

% Construction of the fourth cluster (archimidis spiral)

asp=0.2;

step=(5*pi)/(n_points(4)-1);

count=0;

x_tot=[];

y_tot=[];

for theta=pi:step:6*pi

count=count+1;

r=asp*theta;

x_tot=[x_tot; r*cos(theta)];

y_tot=[y_tot; r*sin(th ...