RankShift: In-Database Detection and Explanation of Categorical Shifts
A login service can receive its usual number of failed sign-ins while one source grows from 2% to 30% of them. The same pattern appears in system logs when a rare event template becomes common while the message rate stays stable. These events change which categories are active without changing how many events occur. RankShift detects such changes inside the analytical database that stores the data. It compares each window's category shares with a benign reference using a Pearson score whose terms identify the categories responsible for the change. The same query returns the score, calibrated alert, and largest increasing contributions. We evaluate RankShift on HDFS, BGL, and Thunderbird. ...
| Authors | Omair Shafi Ahmed |
|---|---|
| Primary category | cs.LG |
| Published | 28 August 2026 |
| Last updated at source | 28 August 2026 |
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