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Machine Learning with R Cookbook, Second Edition

You're reading from Machine Learning with R Cookbook, Second Edition Analyze data and build predictive models

Product type Paperback

Published in Oct 2017

Publisher Packt

ISBN-13 9781787284395

Length 572 pages

Edition 2nd Edition

Languages

R

Tools

Hadoop

Concepts

Machine Learning

Author (1):

Yu-Wei, Chiu (David Chiu)

View More author details

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 FREE CHAPTER

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)

Successive differences and moving averages

A successive difference means the difference between the successive observations. For time series y, the successive difference will be (y2-y1), (y3-y2), (y4-y3).

The moving average is used to understand the direction of the current trend.

The moving average will smooth the data if there is a variation in consecutive points. It will smoothen the curve on the base of the average.

R does not have any direct implementation of the moving average, but zoo and the forecast package provides the various functions to find the moving average.

Getting ready

You have completed the preceding recipes and have my_series and my_series1 in R available.

How to do it...

Perform the following steps with R:

> ma(my_series, order=10) 
Output: 
 
       Jan     Feb     Mar     Apr     May     Jun     Jul     Aug     Sep 
2011      NA      NA      NA      NA      NA 3224.85 3170.25 3097.80 3083.95 
2012 3156.60 3186.45 3157.40 3196.90 3215.05 3227.10 3222.55 3208.00 3281.40...

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Authors (1)

Yu-Wei, Chiu (David Chiu)

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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