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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

What is credit risk?


We have been using this term credit risk since the start of this chapter and many of you might be wondering what exactly does this mean, even though you might have guessed it after reading the previous section. Here, we will be explaining this term clearly so that you will have no problem in understanding the data and its features in the subsequent sections when we will be analyzing the data.

The standard definition of credit risk is the risk of defaulting on a debt which takes place due to the borrower failing to make the required debt payments in time. This risk is taken by the lender since the lender incurs losses of both the principal amount as well as the interest on it.

In our case, we will be dealing with a bank which acts as the financial organization giving out loans to customers who apply for them. Hence, customers who might default on the loan payment would be credit risks for the bank. By analyzing customer data and applying machine learning algorithms on it...

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