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Consider the following set of data points: 1.5 1.0 0.5 0.0 -0.5 -1.0 -1.5 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 Single-linkage, aver

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Clustering is a method to solve problem of unsupervised machine learning.Single linkage,average linkage and complete linkage are algorithms of agglomerative Hierarchical clustering. In agglomerative hierarchical clustering we start with each data point as a single cluster and then iteratively join clusters into bigger clusters untill we reach one single cluster with all the data points.

A.single linkage dendrons since in single linkage the distance between two clusters is the minimum distance between the two groups, i.e. the distance between the data points closest to the other cluster is taken as the distance between the two clusters.Therefore the height of the dendrons connected will be minimum in case of single linkage dendrons.

B. complete linkage dendrons since in complete linkage the distance between the farthest points are taken as the intra cluster distance.Therefore, the height of the dendrons connected will be maximum in case of complete linkage dendrons.

C. average linkage dendrons since in average linkage the distance  between two clusters is defined as the average distance between each point in one cluster to every point in the other cluster.Therefore the height of the dendrons connected will be somewhat in between the complete linkage dendrons abd single linkage dendrons.

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