Question

Which of the following clustering methods can be described as a data transformation based on its manifold followed by running k-means clustering?

a) Hierarchical clustering

b) K-means clustering

c) DBSCAN

d) Spectral clustering

Answer 1

Spectral clustering is the technique that involves a data transformation based on the data's manifold followed by k-means clustering.

Step-by-step explanation:

The clustering method that can be described as a data transformation based on its manifold followed by running k-means clustering is spectral clustering. Spectral clustering techniques work by exploiting the spectrum (eigenvalues) of the similarity matrix of the data to reduce dimensions before applying k-means. The algorithm transforms the data into a space where clusters are more easily identifiable and then applies the k-means algorithm to assign data points to clusters.