between clusters dendrogram(linkage_arraymark the cuts in the tree that signify two or three clusters ax plt gca(bounds ax get_xbound(ax plot(bounds[ ]'--' =' 'ax plot(bounds[ ]'--' =' 'ax text(bounds[ ] two clusters'va='center'fontdict={'size' }ax text(bounds[ ] three clusters'va='center'fontdict={'size' }plt xlabel("sample index"plt ylabel("cluster distance"figure - dendrogram of the clustering shown in figure - with lines indicating splits into two and three clusters the dendrogram shows data points as points on the bottom (numbered from to thena tree is plotted with these points (representing single-point clustersas the leavesand new node parent is added for each two clusters that are joined reading from bottom to topthe data points and are joined first (as you could see in figure - nextpoints and are joined into clusterand so on at the top levelthere are two branchesone consisting of points and and the other consisting of points and these correspond to the two largest clusters in the lefthand side of the plot unsupervised learning and preprocessing