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Machine Learning in Java

You're reading from   Machine Learning in Java Helpful techniques to design, build, and deploy powerful machine learning applications in Java

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Product type Paperback
Published in Nov 2018
Publisher Packt
ISBN-13 9781788474399
Length 300 pages
Edition 2nd Edition
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Authors (2):
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Ashish Bhatia Ashish Bhatia
Author Profile Icon Ashish Bhatia
Ashish Bhatia
Bostjan Kaluza Bostjan Kaluza
Author Profile Icon Bostjan Kaluza
Bostjan Kaluza
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Toc

Table of Contents (13) Chapters Close

Preface 1. Applied Machine Learning Quick Start FREE CHAPTER 2. Java Libraries and Platforms for Machine Learning 3. Basic Algorithms - Classification, Regression, and Clustering 4. Customer Relationship Prediction with Ensembles 5. Affinity Analysis 6. Recommendation Engines with Apache Mahout 7. Fraud and Anomaly Detection 8. Image Recognition with Deeplearning4j 9. Activity Recognition with Mobile Phone Sensors 10. Text Mining with Mallet - Topic Modeling and Spam Detection 11. What Is Next? 12. Other Books You May Enjoy

Customer Relationship Prediction with Ensembles

Any type of company that offers a service, product, or experience needs a solid understanding of their relationship with their customers; therefore, customer relationship management (CRM) is a key element of modern marketing strategies. One of the biggest challenges that businesses face is the need to understand exactly what causes a customer to buy new products.

In this chapter, we will work on a real-world marketing database provided by the French telecom company, Orange. The task will be to estimate the likelihood of the following customer actions:

  • Switch provider (churn)
  • Buy new products or services (appetency)
  • Buy upgrades or add-ons proposed to them to make the sale more profitable (upselling)

We will tackle the Knowledge Discovery and Data Mining (KDD) Cup 2009 challenge and show the steps to process the data using Weka...

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