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You're reading from Machine Learning with R - Third Edition

Product typeBook

Published inApr 2019

Reading LevelIntermediate

PublisherPackt

ISBN-139781788295864

Edition3rd Edition

Languages

Tools

RStudio

Concepts

Machine Learning

Author (1)

Brett Lantz

Example – identifying risky bank loans using C5.0 decision trees

The global financial crisis of 2007-2008 highlighted the importance of transparency and rigor in banking practices. As the availability of credit was limited, banks tightened their lending systems and turned to machine learning to more accurately identify risky loans.

Decision trees are widely used in the banking industry due to their high accuracy and ability to formulate a statistical model in plain language. Since governments in many countries carefully monitor the fairness of lending practices, executives must be able to explain why one applicant was rejected for a loan while another was approved. This information is also useful for customers hoping to determine why their credit rating is unsatisfactory.

It is likely that automated credit scoring models are used for credit card mailings and instant online approval processes. In this section, we will develop a simple credit approval model using C5.0 decision trees. We will...

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Machine Learning with R - Third Edition

Published in: Apr 2019Publisher: PacktISBN-13: 9781788295864

Author (1)

Brett Lantz

Brett Lantz (DataSpelunking) has spent more than 10 years using innovative data methods to understand human behavior. A sociologist by training, Brett was first captivated by machine learning during research on a large database of teenagers' social network profiles. Brett is a DataCamp instructor and a frequent speaker at machine learning conferences and workshops around the world. He is known to geek out about data science applications for sports, autonomous vehicles, foreign language learning, and fashion, among many other subjects, and hopes to one day blog about these subjects at Data Spelunking, a website dedicated to sharing knowledge about the search for insight in data.
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You're reading from Machine Learning with R - Third Edition

Example – identifying risky bank loans using C5.0 decision trees

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Author (1)

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