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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

Updating the counting.py utility

Remember the counting.py utility from Chapter 2? In this section, we are going to update it and use it for some important tasks. We are not going to completely change the existing functionality or throw away all the existing code. We are going to build on the existing code of the counting.py utility, which is a great and productive way to develop new software.

The updated version of the utility can be used for the following tasks:

  • Seeing whether a time series can fit into an iSAX index. This computation is based on the existing functionality of counting.py combined with a test of whether the values of all dictionary entries are smaller than the threshold value.
  • Seeing whether a time series can fit into an iSAX index using more segments or by increasing the threshold. Again, this computation is based on the existing functionality of counting.py, which is enhanced with some extra computations and testing.
  • Seeing whether an iSAX index...
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