Cluster AnalysisCluster Analysis

Purpose• clustering analysis is a process where a set

of objects is partitioned into several clusters

• All members in one cluster are similar to each other and different from the members of other clusters, according to some similarity metric

Cluster Analysis

X (Income)

Y (Age)

Customer(Object)

Variables

Cluster

Dissimilarity (Distance) Measure

Dissimilarity (Distance) Measure

Dissimilarity (Distance) Measure

Categorization of Clustering Methods

• Exclusive vs. Non-Exclusive (Overlapping)• Hierarchical Methods vs. Partitioning Methods• Hierarchical Methods

– Single Link Method– Complete Link Method

• Partitioning Methods– Kohonen Self-Organizing Maps (SOM)– K-Means Methods– K-Medoids Methods (PAM, CLARA, CLARANS)– Demographic Methods– …

Hierarchical Methods

DissimilarityMatrix (55)