Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Practical Machine Learning with R

You're reading from   Practical Machine Learning with R Define, build, and evaluate machine learning models for real-world applications

Arrow left icon
Product type Paperback
Published in Aug 2019
Publisher Packt
ISBN-13 9781838550134
Length 416 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Authors (3):
Arrow left icon
Brindha Priyadarshini Jeyaraman Brindha Priyadarshini Jeyaraman
Author Profile Icon Brindha Priyadarshini Jeyaraman
Brindha Priyadarshini Jeyaraman
Ludvig Renbo Olsen Ludvig Renbo Olsen
Author Profile Icon Ludvig Renbo Olsen
Ludvig Renbo Olsen
Monicah Wambugu Monicah Wambugu
Author Profile Icon Monicah Wambugu
Monicah Wambugu
Arrow right icon
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 FREE CHAPTER 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...
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image