Table 8 Example of results of anomaly rate calculation
From: Anomaly detection in business processes using process mining and fuzzy association rule learning
Anomaly attributes | Cases | ||||
|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | |
Skipped | |||||
 Sequence | 2 | 0 | 0 | 0 | 0 |
 Decision | 0 | 2 | 0 | 0 | 0 |
Wrong throughput time | |||||
 Min | 0 | 0 | 4 | 0 | 0 |
 Max | 0 | 0 | 0 | 5 | 0 |
Wrong resource | 0 | 0 | 0 | 0 | Â |
 Wrong duty | |||||
  Sequence | 0 | 0 | 0 | 0 |  |
  Decision | 0 | 0 | 0 | 0 |  |
  Combine | 0 | 0 | 0 | 0 | 0 |
Wrong pattern | 0 | 2 | 2 | 0 | 0 |
Wrong decision | 0 | 0 | 2 | 0 | 0 |
Rates of anomaly | 0.055 | 0.393 | 0.107 | 0.086 | 0.033 |