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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
Author (1):
Yu-Wei, Chiu (David Chiu) Yu-Wei, Chiu (David Chiu)
Profile icon Yu-Wei, Chiu (David Chiu)
Toc

Table of Contents (21) Chapters close

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)

Plotting and forecasting time series data


Once we have a time series dataset, we want to plot the time series to see the trend. We can also forecast from the given time series.

Getting ready

You have completed the previous recipe and have my_series time series ready. You also need to install a forecast package.

How to do it...

Perform the following steps in R:

> plot(my_series) 

Plot of m y_series

> plot(AirPassengers) 

Plot of AirPassengers

> cycle(AirPassengers) 
Output: 
     Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 
1949   1   2   3   4   5   6   7   8   9  10  11  12 
1950   1   2   3   4   5   6   7   8   9  10  11  12 
1951   1   2   3   4   5   6   7   8   9  10  11  12 
1952   1   2   3   4   5   6   7   8   9  10  11  12 
1953   1   2   3   4   5   6   7   8   9  10  11  12 
1954   1   2   3   4   5   6   7   8   9  10  11  12 
1955   1   2   3   4   5   6   7   8   9  10  11  12 
1956   1   2   3   4   5   6   7   8   9  10  11  12 
1957   1   2   3   4   5   6   7   8...
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