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I haven't looked at the implementation details in the Pig code, but at least in the R interfaces, multivariate dataframes are treated one timeseries at a time.
This is not intuitive given the rational behind using RPCA for anomaly detection, in particular the existence of many dimensional datasets.
A data point that violates the lower dimensional subspace assumption by changing relationship between two variables could be easily missed in a one variable at a time perspective.
The text was updated successfully, but these errors were encountered:
I haven't looked at the implementation details in the Pig code, but at least in the R interfaces, multivariate dataframes are treated one timeseries at a time.
This is not intuitive given the rational behind using RPCA for anomaly detection, in particular the existence of many dimensional datasets.
A data point that violates the lower dimensional subspace assumption by changing relationship between two variables could be easily missed in a one variable at a time perspective.
The text was updated successfully, but these errors were encountered: