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Time Series Indexing

You're reading from   Time Series Indexing Implement iSAX in Python to index time series with confidence

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Product type Paperback
Published in Jun 2023
Publisher Packt
ISBN-13 9781838821951
Length 248 pages
Edition 1st Edition
Languages
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Author (1):
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Mihalis Tsoukalos Mihalis Tsoukalos
Author Profile Icon Mihalis Tsoukalos
Mihalis Tsoukalos
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Table of Contents (11) Chapters Close

Preface 1. Chapter 1: An Introduction to Time Series and the Required Python Knowledge 2. Chapter 2: Implementing SAX FREE CHAPTER 3. Chapter 3: iSAX – The Required Theory 4. Chapter 4: iSAX – The Implementation 5. Chapter 5: Joining and Comparing iSAX Indexes 6. Chapter 6: Visualizing iSAX Indexes 7. Chapter 7: Using iSAX to Approximate MPdist 8. Chapter 8: Conclusions and Next Steps 9. Index 10. Other Books You May Enjoy

Summary

This chapter included the theory behind and practical implementation of SAX and an understanding of a time series from a statistical viewpoint. As the iSAX index construction is based on the SAX representation, we cannot construct an iSAX index without computing SAX representations.

Before you begin reading Chapter 3, please make sure that you know how to calculate the SAX representation of a time series or a subsequence, given the sliding window size, the number of segments, and the cardinality.

The next chapter contains the theory related to the iSAX index, shows you how to manually construct an iSAX index (which you will find very entertaining), and includes the development of some handy utilities.

You have been reading a chapter from
Time Series Indexing
Published in: Jun 2023
Publisher: Packt
ISBN-13: 9781838821951
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