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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

Data sources


Data sources are everywhere. As the following picture tries to suggest, we can find data within all the realms of reality. This hyperbolic sentence is becoming more true thanks to the well-known trend of the internet of things, and now that every kind of object is getting connected to the internet, we are starting to collect data from tons of new physical sources. This data can come in a form already feasible for being collected and stored within our databases, or in a form that needs to be further modified to become usable for our analyses:

We can, therefore, see that between our data sources and the physical data warehouse where they are going to be stored, a small components lies, which is the set of tools and software needed to make data coming from sources storable.

We should note something here—we are not talking about data cleaning and data validation. Those activities will be performed later on by our data mining engine retrieving the data from our data warehouse. For...

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