Table 7 Results of models using MFCC with CTGAN.

From: Improved railway track faults detection using Mel-frequency cepstral coefficient and constant-Q transform features

Model

Class

Precision

Recall

F1 Score

Model

Class

Precision

Recall

F1 Score

DT

0

0.90

0.92

0.91

LR

0

1.00

1.00

1.00

1

1.00

1.00

1.00

1

1.00

1.00

1.00

2

0.92

0.90

0.91

2

1.00

1.00

1.00

Micro avg.

0.94

0.94

0.94

Micro avg.

1.00

1.00

1.00

Weighted avg.

0.94

0.94

0.94

Weighted avg.

1.00

1.00

1.00

Accuracy

0.94

Accuracy

1.00

SVC

0

1.00

1.00

1.00

NB

0

1.00

1.00

1.00

1

1.00

1.00

1.00

1

1.00

1.00

1.00

2

1.00

1.00

1.00

2

1.00

1.00

1.00

Micro avg.

1.00

1.00

1.00

Micro avg.

1.00

1.00

1.00

Weighted avg.

1.00

1.00

1.00

Weighted avg.

1.00

1.00

1.00

Accuracy

1.00

Accuracy

1.00

KNN

0

0.99

1.00

1.00

RF

0

1.00

1.00

1.00

1

1.00

1.00

1.00

1

1.00

1.00

1.00

2

1.00

1.00

1.00

2

1.00

1.00

1.00

Micro avg.

1.00

1.00

1.00

Micro avg.

1.00

1.00

1.00

Weighted avg.

1.00

1.00

1.00

Weighted avg.

1.00

1.00

1.00

Accuracy

1.00

Accuracy

1.00

Hard Voting

0

1.00

1.00

1.00

Soft Voting

0

1.00

1.00

1.00

1

1.00

1.00

1.00

1

1.00

1.00

1.00

2

1.00

1.00

1.00

2

1.00

1.00

1.00

Micro avg.

1.00

1.00

1.00

Micro avg.

1.00

1.00

1.00

Weighted avg.

1.00

1.00

1.00

Weighted avg.

1.00

1.00

1.00

Accuracy

1.00

Accuracy

1.00