[bluechair]

Didn’t see it mentioned but good to know about: UCR matrix profile.

The Matrix Profile is honestly one of the most underrated tools in the time series analysis space - it's ridiculously efficient. The killer feature is how it just works for finding motifs and anomalies without having to mess around with window sizes and thresholds like you do with traditional techniques. Solid across domains too, from manufacturing sensor data to ECG analysis to earthquake detection.

https://www.cs.ucr.edu/~eamonn/MatrixProfile.html

[jmpeax]

What do you mean you don't have to mess around with window sizes? Matrix profile is highly dependent on the window size.

[eamonnkeogh]

The MP is so efficent that you can test ALL window lengths at once! This is called MADRID [a].

[a] Matrix Profile XXX: MADRID: A Hyper-Anytime Algorithm to Find Time Series Anomalies of all Lengths. Yue Lu, Thirumalai Vinjamoor Akhil Srinivas, Takaaki Nakamura, Makoto Imamura, and Eamonn Keogh. ICDM 2023.

[eamonnkeogh]

Thank you for your kind words ;-)

[Croftengea]

MP is one of the best univariate methods, but it's actually mentioned in the article.

[sriram_malhar]

Thanks for sharing; I am most intrigued by the sales pitch. But the website is downright ugly.

This is a better presentation by the same folks. https://matrixprofile.org/

[Croftengea]

I don't think it's being updated. Latest blog posts are from 2020, and Github repos haven't seen commits for the last 5-6 years. MP went a long way since then.

[eskaytwo]

I don’t think it’s the same people.

[sriram_malhar]

Ah, you are right. I got the link from the original URL, so I just assumed. Thanks for the correction.

[willvarfar]

What is the relationship? And why is there a foundation for something like this?

[hoseja]

Are you being serious? The first page actually has information on it. You can add margins in the devtools.

[windsignaling]

Covered in section 6.2.1.

[bee_rider]

What does it do? Anything to do with matrices, like, from math?

[eskaytwo]

It does convolution of each sub sequence across the series length, and then shows the distance of the closest match. This can detect both outliers (long distance from closest match) as well as repeated patterns (short distance).

[belter]

"Introduction to Matrix Profiles" - https://towardsdatascience.com/introduction-to-matrix-profil...