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R Data Mining

You're reading from  R Data Mining

Product type Book
Published in Nov 2017
Publisher Packt
ISBN-13 9781787124462
Pages 442 pages
Edition 1st Edition
Languages
Concepts

Table of Contents (22) Chapters

Title Page
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
Why to Choose R for Your Data Mining and Where to Start A First Primer on Data Mining Analysing Your Bank Account Data The Data Mining Process - CRISP-DM Methodology Keeping the House Clean – The Data Mining Architecture How to Address a Data Mining Problem – Data Cleaning and Validation Looking into Your Data Eyes – Exploratory Data Analysis Our First Guess – a Linear Regression A Gentle Introduction to Model Performance Evaluation Don't Give up – Power up Your Regression Including Multiple Variables A Different Outlook to Problems with Classification Models The Final Clash – Random Forests and Ensemble Learning Looking for the Culprit – Text Data Mining with R Sharing Your Stories with Your Stakeholders through R Markdown Epilogue
Dealing with Dates, Relative Paths and Functions

Further references

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