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Re:Show HN: Fast Anomaly Detection in Graphs [pdf] by rathel on Tuesday April 07, 2020 @01:53PM (#22805649)
Thank you for the explanation.

I'm looking forward to M-Stream for multi-dimensional data - but I have one question for that. Is there some preferred approach for selecting features in multi-dimensional anomaly detection?

Because I wonder if given enough dimensions, everything would be anomalous. Kind of like p-hacking works (at p=0.05 one of twenty hypotheses is falsely accepted just by sheer luck).

Re:Show HN: Fast Anomaly Detection in Graphs [pdf] by siddhartb_ on Tuesday April 07, 2020 @02:08PM (#22805776)
Interesting question. With an increase in dimensions, we consider the correlation between the features in addition to considering them individually. The work is currently under review. Feel free to get in touch and I can update you once we release the MStream work.