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R Data Mining

You're reading from   R Data Mining Implement data mining techniques through practical use cases and real-world datasets

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Product type Paperback
Published in Nov 2017
Publisher Packt
ISBN-13 9781787124462
Length 442 pages
Edition 1st Edition
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Concepts
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Author (1):
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Andrea Cirillo Andrea Cirillo
Author Profile Icon Andrea Cirillo
Andrea Cirillo
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Table of Contents (16) Chapters Close

Preface 1. Why to Choose R for Your Data Mining and Where to Start FREE CHAPTER 2. A First Primer on Data Mining Analysing Your Bank Account Data 3. The Data Mining Process - CRISP-DM Methodology 4. Keeping the House Clean – The Data Mining Architecture 5. How to Address a Data Mining Problem – Data Cleaning and Validation 6. Looking into Your Data Eyes – Exploratory Data Analysis 7. Our First Guess – a Linear Regression 8. A Gentle Introduction to Model Performance Evaluation 9. Don't Give up – Power up Your Regression Including Multiple Variables 10. A Different Outlook to Problems with Classification Models 11. The Final Clash – Random Forests and Ensemble Learning 12. Looking for the Culprit – Text Data Mining with R 13. Sharing Your Stories with Your Stakeholders through R Markdown 14. Epilogue
15. Dealing with Dates, Relative Paths and Functions

Set up an rmarkdown report

No more chatting now! Let's move to the actual production of our report. We are going to use RStudio, so let's open it and create a new R markdown report:

We can now specify what kind of document we want to create, which in our case is a Shiny Document. I write down the title and my name as the author: 

A non-empty template with a file extension as .rmd was just created for us:

I will tell you a bit more about Shiny later when we actually use it, but let me give you just a quick intro to it and R markdown so that you can feel more comfortable in going ahead:

  • R markdown is basically an R package that provides functions to create various kinds of documents hosting both text and R code outputs. It was a father of a prolific family, which nowadays encompasses packages for writing books directly from R to packages for building...
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