a) Clustering is a collection of data objects.
b) Clustering analysis is also known as segmentation.
c) There are no predetermined classes in clustering.
d) Clustering is an unsupervised classification technique.
Given k, the k-means algorithm is implemented in the following steps:
a) Select k initial observations as seeds.
b) Assign each of the other observations to the cluster with the nearest centroid.
c) Recalculate cluster centroids (averages) based on the assignments from step b.
d) Iterate between steps b and c, stop when there are no more new assignments.
e) Select the desired number of clusters k.
f) Calculate average cluster values (cluster centroids) over each variable. For the initial iteration, this will simply be the initial seed observations.