Cluster Analysis
Chapter
16
Cluster Analysis
Identifying groups of individuals or objects that are similar to each other but different from individuals in other groups can be intellectually satisfying, profitable, or sometimes both. Using your customer base, you may be able to form clusters of customers who have similar buying habits or demographics. You can take advantage of these similarities to target offers to subgroups that are most likely to be receptive to them. Based on scores on psychological inventories, you can cluster patients into subgroups that have similar response patterns. This may help you in targeting appropriate treatment and studying typologies of diseases. By analyzing the mineral contents of excavated materials, you can study their origins and spread.
Tip: Although both cluster analysis and discriminant analysis classify objects (or cases) into categories, discriminant analysis requires you to know group membership for the cases used to derive the classification rule. The goal of cluster analysis is to identify the actual groups. For example, if you are interested in distinguishing between several disease groups using discriminant analysis, cases with known diagnoses must be available. Based on these cases, you derive a rule for classifying undiagnosed patients. In cluster analysis, you don’t know who or what belongs in which group. You often don’t even know the number of groups.
Examples
You need to identify people with similar patterns of past purchases so that you can tailor your marketing strategies.
361
362 Chapter 16
You’ve been assigned to group television shows into homogeneous categories based on viewer characteristics. This can be used for market segmentation. You want to cluster skulls excavated from archaeological digs into the civilizations from which they originated. Various measurements of the skulls are available. You’re trying to examine patients with a diagnosis of depression to determine if distinct subgroups can be
16
Cluster Analysis
Identifying groups of individuals or objects that are similar to each other but different from individuals in other groups can be intellectually satisfying, profitable, or sometimes both. Using your customer base, you may be able to form clusters of customers who have similar buying habits or demographics. You can take advantage of these similarities to target offers to subgroups that are most likely to be receptive to them. Based on scores on psychological inventories, you can cluster patients into subgroups that have similar response patterns. This may help you in targeting appropriate treatment and studying typologies of diseases. By analyzing the mineral contents of excavated materials, you can study their origins and spread.
Tip: Although both cluster analysis and discriminant analysis classify objects (or cases) into categories, discriminant analysis requires you to know group membership for the cases used to derive the classification rule. The goal of cluster analysis is to identify the actual groups. For example, if you are interested in distinguishing between several disease groups using discriminant analysis, cases with known diagnoses must be available. Based on these cases, you derive a rule for classifying undiagnosed patients. In cluster analysis, you don’t know who or what belongs in which group. You often don’t even know the number of groups.
Examples
You need to identify people with similar patterns of past purchases so that you can tailor your marketing strategies.
361
362 Chapter 16
You’ve been assigned to group television shows into homogeneous categories based on viewer characteristics. This can be used for market segmentation. You want to cluster skulls excavated from archaeological digs into the civilizations from which they originated. Various measurements of the skulls are available. You’re trying to examine patients with a diagnosis of depression to determine if distinct subgroups can be