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

Product type Paperback

Published in Nov 2017

Publisher Packt

ISBN-13 9781787124462

Length 442 pages

Edition 1st Edition

Languages

Tools

ggplot

Concepts

Data Mining

Author (1):

Andrea Cirillo

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Table of Contents (16) Chapters

Preface

1. Why to Choose R for Your Data Mining and Where to Start

2. A First Primer on Data Mining Analysing Your Bank Account Data FREE CHAPTER

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

Data understanding

Now that the goals and success criteria of our activity are clear, we can start gathering relevant data for our project. Where should we look for this data? Within the resources, we listed the project plan, of course. The first task of this phase will, therefore, be to actually start acquiring from your resources.

Data collection

A core principle to be respected during these activities is replicability—you should carefully take note of all the steps and criteria employed within the data acquisition phase, so that it can be replicated by a third-party, and also by yourself in future, if needed. The typical output of this phase is a data collection phase, where steps and filtering criteria are listed.

How to perform data collection with R

If your data mining project is going to be performed with R, which we could infer from you reading this book, the data collection phase will essentially be performed by downloading your data from its original source, and importing it within...