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Practical Machine Learning with R

You're reading from  Practical Machine Learning with R

Product type Book
Published in Aug 2019
Publisher Packt
ISBN-13 9781838550134
Pages 416 pages
Edition 1st Edition
Languages
Authors (3):
Brindha Priyadarshini Jeyaraman Brindha Priyadarshini Jeyaraman
Profile icon Brindha Priyadarshini Jeyaraman
Ludvig Renbo Olsen Ludvig Renbo Olsen
Profile icon Ludvig Renbo Olsen
Monicah Wambugu Monicah Wambugu
Profile icon Monicah Wambugu
View More author details
Toc

Table of Contents (8) Chapters close

About the Book 1. An Introduction to Machine Learning 2. Data Cleaning and Pre-processing 3. Feature Engineering 4. Introduction to neuralnet and Evaluation Methods 5. Linear and Logistic Regression Models 6. Unsupervised Learning 1. Appendix

Applications of Clustering

Clustering is useful in a variety of fields. We will look at two of them in detail:

  • Market segmentation: Segmentation is the process of splitting a heterogeneous group of consumers or customers into smaller homogeneous groups. These smaller groups can be targeted differently based on their characteristics and behavior. Segmentation is important to businesses because it shapes both marketing efforts and product development. Businesses designing products must decide which product is targeted to which segment of consumers or customers. They must consequently decide what features to include, how to price the product, and how to take it to market. All these actions are heavily influenced by the characteristics of the different segments.

    Most businesses start off not knowing how to group their customers. Clustering is useful in helping these businesses to identify segments in their data.

  • Document clustering and information retrieval: In the information and knowledge...
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