Table 6 Performance comparison in holdout test set.

From: Student dropout prediction through machine learning optimization: insights from moodle log data

Week

Model

F1-score

Recall

Accuracy

AUC

Approved

Reproved

Approved

Reproved

1

Multiple

0.63

0.49

0.56

0.60

0.57

0.63

Unique

0.73

0.51

0.73

0.50

0.65

0.66

3

Multiple

0.82

0.57

0.86

0.51

0.75

0.74

Unique

0.83

0.58

0.88

0.57

0.76

0.84

5

Multiple

0.82

0.55

0.78

0.63

0.74

0.76

Unique

0.92

0.74

0.94

0.68

0.86

0.92

7

Multiple

0.91

0.79

0.89

0.82

0.87

0.90

Unique

0.94

0.86

0.95

0.85

0.90

0.95

9

Multiple

0.90

0.74

0.95

0.65

0.85

0.90

Unique

0.97

0.94

0.96

0.93

0.95

1.00

11

Multiple

0.76

0.58

0.70

0.68

0.69

0.78

Unique

0.89

0.81

0.98

0.91

0.94

0.98

13

Multiple

0.92

0.67

0.92

0.64

0.87

0.88

Unique

0.98

0.96

1.00

0.93

0.99

0.97

15

Multiple

0.94

0.82

0.96

0.77

0.91

0.98

Unique

0.96

0.91

0.97

0.89

0.95

0.99

  1. Unique model versus multiple models for each week. Significant values are in bold.