Data Science Asked on April 21, 2021
I would like to visualize a large amount of events composed of time serie windows. A typical event would be:
Problem is, my events are not synchronized, and so if I plot them all, it would look like:
Question
Is there any way to visualize all my events so I can see their original/"typical" shape (preferably in the time domain) despite their unsynchronization ?
What I have tried so far:
mean
, median
, p95
,… Problem is, using this approach gives a deformed rendering of the data because of the unsynchronization:What I have thought about
The main problem of applying the mean
, p95
or whatever statistical function is that it is applied along an axis that is not synchronized between events. I don’t know if it exists or if it is even feasible, but I was thinking about an approach that would display those statistical values checking their temporal neighbors ? I know Dynamic Time Warping deals with this unsynchronization but I am not sure if and how I could use it to plot my events in the way I’d like.
An idea of a possible output could be (any other output idea is welcomed!):
Any help, idea, would be greatly appreciated ! Thanks
As far as estimating similarity between the time series series there is a variety of methods you may want to investigate. Some of those are:
Answered by hH1sG0n3 on April 21, 2021
Get help from others!
Recent Answers
Recent Questions
© 2024 TransWikia.com. All rights reserved. Sites we Love: PCI Database, UKBizDB, Menu Kuliner, Sharing RPP