Question

Which of the following is true for partition-based clustering but not hierarchical nor density based clustering algorithnis? a) Partition-based clustering produces sphere-like clusters. b) Partition-based clustering can handle spatial clusters and noisy data. c) Partition-based clustering produces arbitrary shaped clusters. d) Partition-based clustering is a type of unsupervised learning algorithm.

Answer 1

The option that is true for partition-based clustering but not hierarchical nor density based clustering algorithm is

a) Partition-based clustering produces sphere-like clusters.

Partition-based clustering algorithms, such as K-means, tend to produce clusters that are spherical or hyper-spherical in shape. This is because these algorithms assign data points to the cluster whose centroid is nearest, and the centroid is a central point that influences the shape of the resulting cluster.

In contrast, hierarchical clustering and density-based clustering algorithms can produce clusters of arbitrary shapes allowing them to capture more complex structures in the data.