PDC 2020

Comparing process discovery algorithms

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Comparing process discovery algorithms

aXfYnZ

Classification of Split Miner 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, Split Miner

Classification of Log Skeleton (5% noise) 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 (5% noise)

Accuracy of Log Skeleton (5% noise) on aXfYnZ data set

August 27, 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, aXfYnZ, Log Skeleton (5% noise)

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

Classification of Inductive Miner (OR) 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, Inductive Miner (OR)

Classification of Inductive Miner 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, Inductive Miner

Classification of Hybrid ILP Miner 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, Hybrid ILP Miner

Classification of Fodina Miner 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, Fodina Miner

Classification of Alpha Miner 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: Alpha Miner, aXfYnZ, Classification

Accuracy of Split Miner on aXfYnZ 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, aXfYnZ, Split Miner
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Recent Posts

  • F-score of all miners on PDC 2020 data set
  • F-score of Alpha Miner on PDC 2020 data set
  • F-score of Fodina Miner on PDC 2020 data set
  • F-score of Hybrid ILP Miner on PDC 2020 data set
  • F-score of Inductive Miner on PDC 2020 data set

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