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Fitness on Alpha and Inductive models - measured by token-based replay and alignments
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log fitness_token_alpha times_tokenreplay_alpha fitness_token_imdf times_tokenreplay_imdf fitness_align_imdf times_alignments_imdf
03_repairExample.xes.gz 0.000 0.061 99.819 0.107 99.819 0.450
07_bpic2013_problems.xes.gz 0.000 0.185 69.065 0.357 69.065 21.773
04_reviewing.xes.gz 100.000 0.164 0.000 0.201 0.000 12.864
09_a32f0n00.xes.gz 69.100 1.547 100.000 1.764 100.000 11.980
06_bpic2013_incidents.xes.gz 0.013 2.268 26.225 5.302 26.225 356.901
05_bpic2017.xes.gz 0.000 0.371 100.000 0.323 100.000 0.219
02_teleclaims.xes.gz 5.552 0.068 43.736 0.063 43.736 0.189
01_running-example.xes.gz 100.000 0.003 100.000 0.004 100.000 0.011
08_receipt.xes.gz 0.000 0.196 99.791 0.166 99.791 1.709
Precision measured by ETConformance where activated transitions are retrieved using token replay
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log precision_alpha precision_imdf
03_repairExample.xes.gz 0.983 0.246
07_bpic2013_problems.xes.gz 0.000 0.836
04_reviewing.xes.gz 0.738 0.680
09_a32f0n00.xes.gz 0.603 0.480
06_bpic2013_incidents.xes.gz 0.000 0.405
05_bpic2017.xes.gz 0.641 0.760
02_teleclaims.xes.gz 0.327 0.164
01_running-example.xes.gz 0.733 0.733
08_receipt.xes.gz 0.999 0.156
Generalization based on token replay transition recall
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log generalization_alpha generalization_imdf
03_repairExample.xes.gz 0.967 0.966
07_bpic2013_problems.xes.gz 0.849 0.861
04_reviewing.xes.gz 0.895 0.829
09_a32f0n00.xes.gz 0.963 0.945
06_bpic2013_incidents.xes.gz 0.864 0.894
05_bpic2017.xes.gz 0.991 0.985
02_teleclaims.xes.gz 0.978 0.951
01_running-example.xes.gz 0.526 0.550
08_receipt.xes.gz 0.755 0.853
Simplicity based on inverse arc degree
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log simplicity_alpha simplicity_imdf
03_repairExample.xes.gz 0.667 0.667
07_bpic2013_problems.xes.gz 1.000 0.778
04_reviewing.xes.gz 0.725 0.750
09_a32f0n00.xes.gz 0.800 0.778
06_bpic2013_incidents.xes.gz 0.789 0.649
05_bpic2017.xes.gz 0.267 0.655
02_teleclaims.xes.gz 0.339 0.642
01_running-example.xes.gz 0.652 0.806
08_receipt.xes.gz 0.160 0.606