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Machine Learning with R Cookbook, Second Edition - Second Edition

You're reading from Machine Learning with R Cookbook, Second Edition - Second Edition

Product type Book

Published in Oct 2017

Publisher Packt

ISBN-13 9781787284395

Pages 572 pages

Edition 2nd Edition

Languages

Concepts

Machine Learning

Author (1):

Yu-Wei, Chiu (David Chiu)

Table of Contents (21) Chapters

Title Page

Credits

About the Authors

About the Reviewers

www.PacktPub.com

Customer Feedback

Preface

1. Practical Machine Learning with R

2. Data Exploration with Air Quality Datasets

3. Analyzing Time Series Data

4. R and Statistics

5. Understanding Regression Analysis

6. Survival Analysis

7. Classification 1 - Tree, Lazy, and Probabilistic

8. Classification 2 - Neural Network and SVM

9. Model Evaluation

10. Ensemble Learning

11. Clustering

12. Association Analysis and Sequence Mining

13. Dimension Reduction

14. Big Data Analysis (R and Hadoop)

Fitting multiple regression

Multiple regression includes multiple predictors and using the same lm function we can create a model.

Getting ready

You have completed the previous recipes and have installed the car package. You are also aware of using the lm function. In this recipe, we will use the Prestige dataset from the car package.

How to do it...

Perform the following step to perform multiple regression with lm:

> head(Prestige)
Output:
 education income women prestige census type
gov.administrators 13.11 12351 11.16 68.8 1113 prof
general.managers 12.26 25879 4.02 69.1 1130 prof
accountants 12.77 9271 15.70 63.4 1171 prof
purchasing.officers 11.42 8865 9.11 56.8 1175 prof
chemists 14.62 8403 11.68 73.5 2111 prof
physicists 15.64 11030 5.13 77.6 2113 prof
> str(Prestige)
Output
'data.frame': 102 obs. of 6 variables:
 $ education: num 13.1 12.3 12.8 11.4 14.6 ...
 $ income : int 12351 25879 9271 8865 8403 11030 8258 14163 11377 11023 ...
 $ women : num 11.16 4.02 15.7 9.11 11.68 .....

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Authors (1)

Yu-Wei, Chiu (David Chiu)

Yu-Wei, Chiu (David Chiu) is the founder of LargitData (www.LargitData.com), a startup company that mainly focuses on providing big data and machine learning products. He has previously worked for Trend Micro as a software engineer, where he was responsible for building big data platforms for business intelligence and customer relationship management systems. In addition to being a start-up entrepreneur and data scientist, he specializes in using Spark and Hadoop to process big data and apply data mining techniques for data analysis. Yu-Wei is also a professional lecturer and has delivered lectures on big data and machine learning in R and Python, and given tech talks at a variety of conferences. In 2015, Yu-Wei wrote Machine Learning with R Cookbook, Packt Publishing. In 2013, Yu-Wei reviewed Bioinformatics with R Cookbook, Packt Publishing. For more information, please visit his personal website at www.ywchiu.com. **********************************Acknowledgement************************************** I have immense gratitude for my family and friends for supporting and encouraging me to complete this book. I would like to sincerely thank my mother, Ming-Yang Huang (Miranda Huang); my mentor, Man-Kwan Shan; the proofreader of this book, Brendan Fisher; Members of LargitData; Data Science Program (DSP); and other friends who have offered their support.

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