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Business Intelligence by Jerzy Surma

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4.3. Cluster Analysis

Cluster analysis consists of finding in a set of objects subsets (groups) that have common attributes (features). The cluster analysis algorithm aims to divide a set of objects into subsets in which interclass similarity is maximized and intraclass similarity is minimized. Whereas in a classification task you have to classify objects, in clustering your task is to find classes into which objects can be divided. That is why learning classification principles are called supervised learning and the identification of groups of objects is called unsupervised learning.

The key issue in cluster analysis is finding similarity between objects. If objects are described by quantitative attributes (sales amount, financial liquidity, ...

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