0
$\begingroup$

I have multivariate timeseries data represented in matrix format. I have matrix A of MxN where M is number of timestamp and N is number of sensor. Time series data is sampled at very 1 hour.
Each column vector represents single timeseries data . If I do K rank approximation using SVD and I get

A=UΣV∗

With K rank approximation I select first K columns of matrix U. How do I interpret this result in terminology of sensors data and timeseries.

Thanks in advance

Improve this question
$\endgroup$

0

Reset to default

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy