Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
Arrow left icon
All Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletter Hub
Free Learning
Arrow right icon
timer SALE ENDS IN
0 Days
:
00 Hours
:
00 Minutes
:
00 Seconds
Arrow up icon
GO TO TOP
R Data Mining

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

Arrow left icon
Product type Paperback
Published in Nov 2017
Publisher Packt
ISBN-13 9781787124462
Length 442 pages
Edition 1st Edition
Languages
Tools
Concepts
Arrow right icon
Author (1):
Arrow left icon
Andrea Cirillo Andrea Cirillo
Author Profile Icon Andrea Cirillo
Andrea Cirillo
Arrow right icon
View More author details
Toc

Table of Contents (22) Chapters Close

Title Page
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
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

Summary


By the end of this chapter, you may feel like the adrenaline accumulated within the first two has got a bit diluted, but you would be wrong. This chapter was all about discovering the basic ingredients of a well-conceived and well-conducted data mining project, namely:

  • The data sources (where to find data to answer your questions)
  • The data warehouse (where to properly store your data to have it at your disposal when needed)
  • The data mining engine (to perform your data modelling activities, and get knowledge from your data)
  • The user interface (to interact with your engine)

We are now ready to leave the quiet village where our apprentice took place, where we discovered our weapon, its power and the way to use it. A real and complex problem is waiting for us just on the next page. Good luck, my dear reader. 

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $15.99/month. Cancel anytime
Visually different images