Mashinali o‘qitishga kirish Nosirov Xabibullo xikmatullo o‘gli Falsafa doktori (PhD), tret kafedrasi mudiri

ptsymb = {'bs','r^','md','go','c+'};

for i = 1:2

clust = find(cidx2==i); plot3(meas(clust,1),meas(clust,2),meas(clust,3),ptsymb{i});

hold on

end

plot3(cmeans2(:,1),cmeans2(:,2),cmeans2(:,3),'ko'); plot3(cmeans2(:,1),cmeans2(:,2),cmeans2(:,3),'kx');

hold off

xlabel('Sepal Length');

ylabel('Sepal Width'); zlabel('Petal Length'); view(-137,10);

grid on

Clustering Fisher's Iris Data Using K-Means Clustering

The centroids of each cluster are plotted using circled X's. Three of the points from the lower cluster (plotted with triangles) are very close to points from the upper cluster (plotted with squares). Because the upper cluster is so spread out, those three points are closer to the centroid of the lower cluster than to that of the upper cluster, even though the points are separated from the bulk of the points in their own cluster by a gap. Because K-means clustering only considers distances, and not densities, this kind of result can occur.

You can increase the number of clusters to see if kmeans can find further grouping structure in the data. This time, use the optional 'Display' name-value pair argument to print out information about each iteration in the clustering algorithm.

Clustering Fisher's Iris Data Using K-Means Clustering

[cidx3,cmeans3] = kmeans(meas,3,'Display','iter');

Clustering Fisher's Iris Data Using K-Means Clustering

At each iteration, the kmeans algorithm (see Algorithms) reassigns points among clusters to decrease the sum of point-to-centroid distances, and then recomputes cluster centroids for the new cluster assignments. Notice that the total sum of distances and the number of reassignments decrease at each iteration until the algorithm reaches a minimum. The algorithm used in kmeans consists of two phases. In the example here, the second phase of the algorithm did not make any reassignments, indicating that the first phase reached a minimum after only a few iterations.