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R Data Analysis Projects

You're reading from   R Data Analysis Projects Build end to end analytics systems to get deeper insights from your data

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Product type Paperback
Published in Nov 2017
Publisher Packt
ISBN-13 9781788621878
Length 366 pages
Edition 1st Edition
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Author (1):
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Gopi Subramanian Gopi Subramanian
Author Profile Icon Gopi Subramanian
Gopi Subramanian
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Toc

Table of Contents (9) Chapters Close

Preface 1. Association Rule Mining FREE CHAPTER 2. Fuzzy Logic Induced Content-Based Recommendation 3. Collaborative Filtering 4. Taming Time Series Data Using Deep Neural Networks 5. Twitter Text Sentiment Classification Using Kernel Density Estimates 6. Record Linkage - Stochastic and Machine Learning Approaches 7. Streaming Data Clustering Analysis in R 8. Analyze and Understand Networks Using R

Use case and data


Category management is analyzing a discrete set of similar or related items sold by a retailer, grouped together, as a strategic business unit. This allows the retailer to then evaluate these units by their turnover and profitability. Brain F. Harris is the inventor of the study of category management. His eight-step process, famously called the Brain Harris model, is used widely today. For more information about category management, refer to http://www.nielsen.com/tw/en/insights/reports/2014/category-management-the-win-win-platform-for-manufacturers-and-retailers.html.

The Nielsen definition of a category is based on product features. Products that exhibit the following features are put under the same category:

  • They should meet similar end-consumer needs
  • Products should be interrelated, for example, substitutable
  • We should be able to place the products together on a retailer shelf

When analyzing purchasing behavior, several patterns emerge; some products are  sold together...

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