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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

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