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Time Series Indexing

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

Product type Paperback

Published in Jun 2023

Publisher Packt

ISBN-13 9781838821951

Length 248 pages

Edition 1st Edition

Languages

Python

Concepts

Data Science

Author (1):

Mihalis Tsoukalos

View More author details

Table of Contents (11) Chapters

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

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Summary

Visualization offers a great way to understand your data. Similarly, visualization is a great way to understand the structure of an iSAX index, especially a big one. In this chapter, we saw various ways to visualize an iSAX index with the help of the D3.js JavaScript library and got a better look at the distribution of the subsequences and the height of iSAX indexes.

However, it would be great to try your own visualizations using the D3.js JavaScript library, R, or other appropriate Python packages, which can also create impressive visualizations.

Lastly, do not underestimate the power of a good visualization as it can reveal lots of information in an easy-to-discover way. Just keep in mind that visualization is an art that is hard to master.

The next chapter is about using iSAX indexes for the approximate calculation of the Matrix Profile and the MPdist distance.

The rest of the chapter is locked

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Authors (1)

Mihalis Tsoukalos

Mihalis Tsoukalos

Mihalis Tsoukalos holds a BSc in Mathematics from the University of Patras and an MSc in IT from University College London, UK. His books, Go Systems Programming and Mastering Go, have become must-reads for Unix and Linux systems professionals. He enjoys writing technical articles and has written for Sys Admin, MacTech, C/C++ Users Journal, USENIX ;login:, Linux Journal, Linux User and Developer, Linux Format, and Linux Voice. His research interests include time series data mining, time series indexing, and databases.

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