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Machine Learning with R

You're reading from   Machine Learning with R Learn techniques for building and improving machine learning models, from data preparation to model tuning, evaluation, and working with big data

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Product type Paperback
Published in May 2023
Publisher Packt
ISBN-13 9781801071321
Length 762 pages
Edition 4th Edition
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Author (1):
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Brett Lantz Brett Lantz
Author Profile Icon Brett Lantz
Brett Lantz
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Table of Contents (18) Chapters Close

Preface 1. Introducing Machine Learning 2. Managing and Understanding Data FREE CHAPTER 3. Lazy Learning – Classification Using Nearest Neighbors 4. Probabilistic Learning – Classification Using Naive Bayes 5. Divide and Conquer – Classification Using Decision Trees and Rules 6. Forecasting Numeric Data – Regression Methods 7. Black-Box Methods – Neural Networks and Support Vector Machines 8. Finding Patterns – Market Basket Analysis Using Association Rules 9. Finding Groups of Data – Clustering with k-means 10. Evaluating Model Performance 11. Being Successful with Machine Learning 12. Advanced Data Preparation 13. Challenging Data – Too Much, Too Little, Too Complex 14. Building Better Learners 15. Making Use of Big Data 16. Other Books You May Enjoy
17. Index

Finding teen market segments using k-means clustering

Interacting with friends on a social networking service (SNS), such as Facebook, TikTok, and Instagram, has become a rite of passage for teenagers around the world. Having a relatively large amount of disposable income, these adolescents are a coveted demographic for businesses hoping to sell snacks, beverages, electronics, entertainment, and hygiene products.

The many millions of teenage consumers using such sites have attracted the attention of marketers struggling to find an edge in an increasingly competitive market. One way to gain this edge is to identify segments of teenagers who share similar tastes, so that clients can avoid targeting advertisements to teens with no interest in the product being sold. If it costs 10 dollars to display an advertisement to 1,000 website visitors—a measure of cost per impression—the advertising budget will stretch further if we are selective about who is targeted. For instance...

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