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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

Data Mining

Table of Contents (22) Chapters

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

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

What is R?

Let's start from the very beginning, What exactly is R? You will have read a lot about it on data analysis and data science blogs and websites, but perhaps you are still not able to fix the concept in your mind. R is a high-level programming language. This means that by passing the kind of R scripts you are going to learn in this book, you will be able to order your PC to execute some desired computations and operations, resulting in some predefined output.

Programming languages are a set of predefined instructions that the computer is able to understand and react to, and R is one of them. You may have noticed that I referred to R as a high-level programming language. What does high-level mean? One way to understand it is by comparing it to typical industrial company structures. Within such companies, there is usually a CEO, senior managers, heads of departments, and so on, level by level until we reach the final group of workers.

What is the difference between those levels of a company hierarchy? The CEO makes the main strategical decisions, developing a strategical plan without taking care of tactical and operational details. From there, the lower you go in the hierarchy described, the more tactical and operational decisions become, until you reach the base worker, whose main duty is to execute basic operations, such as screwing and hammering.

It is the same for programming languages:

High-level programming languages are like the CEO; they abstract from operational details, stating high-level sentences which will then be translated by lower-level languages the computer is able to understand
Low-level programming languages are like the heads of departments and workers; they take sentences from higher-level languages and translate them into chunks of instructions needed to make the computer actually produce the output the CEO is looking for

To be precise, we should specify that it is also possible to directly write code using low-level programming languages. Nevertheless, since they tend to be more complex and wordy, their popularity has declined over time.

Now that we have a clear idea of what R is, let's move on and acquire a bit of knowledge about where R came from and when.