PDC 2020

Comparing process discovery algorithms

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Comparing process discovery algorithms

Log Skeleton

F-score of Log Skeleton on PDC 2020 data set

January 22, 2020 by Eric Leave a Comment

This graph shows the F-score values over three different runs for different categories of models. This graph shows the F-score values over three different runs for the situation without noise and with noise. For example, it shows that if there is no noise accuracy may be 100% and is at least 80%, but adding noise … [Read more…]

Posted in: F-score, Log Skeleton, PDC 2020

Classification of Log Skeleton on PDC 2020 data set

August 27, 2019 by Eric Leave a Comment

These graphs show the aggregated classification over three different runs, where for every category (FN, TP, TN, FP) the minimal number over the different runs is taken. For example, if 500 traces are TP in the first run, 490 in the second, and 495 in the third, then the value 490 is used as aggregated … [Read more…]

Posted in: Classification, Log Skeleton, PDC 2020

Classification of Log Skeleton on PDC 2019 data set

August 27, 2019 by Eric Leave a Comment

These graphs show the aggregated classification over three different runs, where for every category (FN, TP, TN, FP) the minimal number over the different runs is taken. For example, if 45 traces are TP in the first run, 40 in the second, and 42 in the third, then the value 40 is used as aggregated … [Read more…]

Posted in: Classification, Log Skeleton, PDC 2019

Classification of Log Skeleton on PDC 2017 data set

August 27, 2019 by Eric Leave a Comment

These graphs show the aggregated classification over three different runs, where for every category (FN, TP, TN, FP) the minimal number over the different runs is taken. For example, if 10 traces are TP in the first run, 0 in the second, and 9 in the third, then the value 8 is used as aggregated … [Read more…]

Posted in: Classification, Log Skeleton, PDC 2017

Classification of Log Skeleton on PDC 2016 data set

August 27, 2019 by Eric Leave a Comment

These graphs show the aggregated classification over three different runs, where for every category (FN, TP, TN, FP) the minimal number over the different runs is taken. For example, if 10 traces are TP in the first run, 8 in the second, and 9 in the third, then the value 8 is used as aggregated … [Read more…]

Posted in: Classification, Log Skeleton, PDC 2016

Classification of Log Skeleton on aXfYnZ data set

August 27, 2019 by Eric Leave a Comment

These graphs show the aggregated classification over three different runs, where for every category (FN, TP, TN, FP) the minimal number over the different runs is taken. For example, if 500 traces are TP in the first run, 490 in the second, and 495 in the third, then the value 490 is used as aggregated … [Read more…]

Posted in: aXfYnZ, Classification, Log Skeleton

Accuracy of Log Skeleton on PDC 2020 data set

August 12, 2019 by Eric Leave a Comment

This graph shows the average accuracy values over three different runs for different categories of models. This graph shows the average accuracy values over three different runs for the situation without noise and with noise. For example, it shows that if there is no noise accuracy may be 100%, but adding noise results in a … [Read more…]

Posted in: Accuracy, Log Skeleton, PDC 2020

Accuracy of Log Skeleton on PDC 2019 data set

July 26, 2019 by Eric Leave a Comment

This graph shows the average accuracy values over three different runs for different models. This graph shows the average accuracy values over three different runs for different categories of models.

Posted in: Accuracy, Log Skeleton, PDC 2019

Accuracy of Log Skeleton on PDC 2017 data set

July 25, 2019 by Eric Leave a Comment

This graph shows the average accuracy values over three different runs for different categories of models.

Posted in: Accuracy, Log Skeleton, PDC 2017

Accuracy of Log Skeleton on PDC 2016 data set

July 25, 2019 by Eric Leave a Comment

This graph shows the average accuracy values over three different runs for different categories of models.

Posted in: Accuracy, Log Skeleton, PDC 2016
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Recent Posts

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