Skip to main content

Table 1 Best performance for each classifier and number of features used to yield the same result. SVM = Support Vector Machine; MLP = Multilayer Perceptron; Instance-Based Algorithm (IBA) derived from k-nearest neighbors (IBk) (k = 1, k = 3, k = 5); AUC = Area under the ROC curve

From: Machine learning techniques for computer-aided classification of active inflammatory sacroiliitis in magnetic resonance imaging

Classifier

Metric name

Metric value

Number of features

SVM

AUC

0.867

2

Sensitivity

0.850

2

Specificity

0.960

1

IBk with k = 1

AUC

0.900

6

Sensitivity

0.850

6

Specificity

0.923

6

IBk with k = 3

AUC

0.932

5

Sensitivity

0.850

3

Specificity

1.000

24

IBk with k = 5

AUC

0.915

2

Sensitivity

0.800

5

Specificity

1.000

17

MLP

AUC

0.926

158

Sensitivity

0.85

150

Specificity

0.923

16