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Table 7 Comparing each baseline meta-model against AeKNN on the 20-benchmark datasets. Listed are the number of datasets where each meta-model produced better predictions than AeKNN (Wins), worse predictions (Losses), or more accurate predictions than all of the other 3 meta-models (Champion)

From: Autoencoder-kNN meta-model based data characterization approach for an automated selection of AI algorithms

Meta-model

Wins

Losses

Champion

Acc

F1-score

AUC

Acc

F1-score

AUC

Acc

F1-score

AUC

AeKNN

-

-

-

-

-

-

16

17

14

KNN

1

2

 

19

18

17

1

2

3

RF

0

0

 

20

20

20

0

0

0

XGB

3

1

 

17

19

17

3

1

3

  1. The best ones are highlighted in bold