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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

Looking into Your Data Eyes – Exploratory Data Analysis

Well done [your name here]: that data was really messy and you did an excellent job getting it ready for the EDA. Just send it to Francis and take his side: he will show you how those kinds of things are performed. We do not have too much time to invest in your education now, but siding him will be useful for you anyway.

Once the boss is done complimenting you, you can send the clean data to Francis and reach his desk.

Hi there, so you did the job with this dirty data. Well done! We are now going to perform some Exploratory Data Analysis, to get a closer look at our data, and to understand where this profit drop came from.

So, that is what EDA stands for: Exploratory Data Analysis. But, let Francis introduce you into this new world: EDA is a powerful tool in our hands. In the beginning of data analysis, analysts...

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