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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

How the sliding window size affects the iSAX construction speed

In this section, we are going to continue working with the accessSplit.py utility we developed in the previous chapter to find out whether the sliding window size affects the construction speed of an iSAX index, provided that the remaining iSAX parameters stay the same.

Put simply, we will use different methods to find out more about the quality of iSAX indexes and whether the sliding window size affects the construction speed. We are going to perform our experiments using the following sliding window sizes: 16, 256, 1024, 4096, and 16384. We are going to experiment using the 500k.gz time series from Chapter 4, 8 segments, a maximum cardinality value of 32, and a threshold value of 500.

For the window size of 16, the results are the following:

$ ./accessSplit.py -s 8 -c 32 -t 500 -w 16 500k.gz
Max Cardinality: 32 Segments: 8 Sliding Window: 16 Threshold: 500 Default Promotion: False
Number of splits: 1376
Number...
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