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 |
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Title of host publication | Practical Graph Mining with R |
Pages | 205-238 |
Number of pages | 34 |
ISBN (Electronic) | 9781439860854 |
DOIs | |
State | Published - Jan 1 2013 |
Bibliographical note
Publisher Copyright:© 2014 by Taylor and Francis Group, LLC.
ASJC Scopus subject areas
- General Economics, Econometrics and Finance
- General Business, Management and Accounting
- General Computer Science