Cluster Analysis

Kanchana Padmanabhan; Brent Harrison; Kevin Wilson; Michael L. Warren; Katie Bright; Justin Mosiman; Jayaram Kancherla; Hieu Phung; Benjamin Miller; Sam Shamseldin

doi:10.1201/b15352-12

Cluster Analysis

Kanchana Padmanabhan, Brent Harrison, Kevin Wilson, Michael L. Warren, Katie Bright, Justin Mosiman, Jayaram Kancherla, Hieu Phung, Benjamin Miller, Sam Shamseldin

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

In Chapter 9, classification was defined as the process of assigning discrete class labels to sets of data. However, what if we do not know what these class labels should be or do not have a training set of data with known relationships? In this case, we wish to group input data together by some measure of similarity. The process of dividing the data into subsets, where each element is as learning.

Original language	English
Title of host publication	Practical Graph Mining with R
Pages	205-238
Number of pages	34
ISBN (Electronic)	9781439860854
DOIs	https://doi.org/10.1201/b15352-12
State	Published - Jan 1 2013

Bibliographical note

Publisher Copyright:
© 2014 by Taylor and Francis Group, LLC.

ASJC Scopus subject areas

Economics, Econometrics and Finance (all)
Business, Management and Accounting (all)
Computer Science (all)

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10.1201/b15352-12

Cite this

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AU - Mosiman, Justin

AU - Kancherla, Jayaram

AU - Phung, Hieu

AU - Miller, Benjamin

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Cluster Analysis

Abstract

Bibliographical note

ASJC Scopus subject areas

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