n analyst segments customers into groups from data without a response variable using the hierarchical clustering algorithm with the Euclidean distance metric. Should we use this result? We should not use this result, since this is a supervised learning problem, and we should have used a different method. We should use this result, because hierarchical clustering creates clusters based on a statistically significant criterion. We should not use this result unless the grouping provides novel business insight, which may require trying different clustering algorithms and different ways to cut the dendrogram into groups.

Answered: analyst segments customers into groups…

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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n analyst segments customers into groups from data without a response variable using the hierarchical clustering algorithm with the Euclidean distance metric. Should we use this result?

		We should not use this result, since this is a supervised learning problem, and we should have used a different method.
		We should use this result, because hierarchical clustering creates clusters based on a statistically significant criterion.
		We should not use this result unless the grouping provides novel business insight, which may require trying different clustering algorithms and different ways to cut the dendrogram into groups.

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