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R Machine Learning By Example

You're reading from   R Machine Learning By Example Understand the fundamentals of machine learning with R and build your own dynamic algorithms to tackle complicated real-world problems successfully

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Product type Paperback
Published in Mar 2016
Publisher
ISBN-13 9781784390846
Length 340 pages
Edition 1st Edition
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Author (1):
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Raghav Bali Raghav Bali
Author Profile Icon Raghav Bali
Raghav Bali
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Table of Contents (10) Chapters Close

Preface 1. Getting Started with R and Machine Learning FREE CHAPTER 2. Let's Help Machines Learn 3. Predicting Customer Shopping Trends with Market Basket Analysis 4. Building a Product Recommendation System 5. Credit Risk Detection and Prediction – Descriptive Analytics 6. Credit Risk Detection and Prediction – Predictive Analytics 7. Social Media Analysis – Analyzing Twitter Data 8. Sentiment Analysis of Twitter Data Index

Detecting and predicting trends

In this section, we will talk about what exactly we mean by trends and how the retailers detect and predict these trends. Basically, a trend in the retail context can be defined as a specific pattern or behavior which occurs over a period of time. This may involve a product or a combination of products being sold out in a very short period of time or even the reverse. A simple example would be a best-selling smartphone being prebooked and out of stock before even hitting the shelves on any e-commerce marketplace, or a combination of products like the classic beer and diapers combination which is frequently found in shopping baskets or carts of customers!

How can we even start analyzing shopping carts or start to detect and predict shopping trends. Like I mentioned earlier, we can achieve this with a combination of the right data and algorithms. Let's assume that we are heading a large retail chain. First we will have to keep track of each and every transaction...

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