Table 2.
Performance measures of data mining algorithm at different levels of significance over Type 1 diabetes dataset
|
SIGNIFICANCE |
p < 5 x 10-13 |
p < 5 x 10-10 |
p < 5 x 10-7 |
p < 5 x 10-4 |
|
||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Algorithm | Acc. | Sp | Sn | AUC | Acc. | Sp | Sn | AUC | Acc. | Sp | Sn | AUC | Acc | Sp | Sn | AUC | Avg. |
|
SLR |
87.5 |
85.0 |
89.7 |
0.93 |
92.5 |
90.2 |
94.9 |
0.97 |
92.5 |
92.0 |
92.0 |
0.96 |
92.5 |
90.0 |
94.9 |
0.96 |
92.2 |
|
Naïve Bayes |
90.0 |
85.4 |
95.0 |
0.97 |
91.3 |
90.2 |
92.3 |
0.98 |
92.5 |
90.2 |
95.0 |
0.96 |
89.0 |
85.4 |
92.3 |
0.92 |
92.0 |
|
SVM |
88.8 |
82.9 |
94.9 |
0.89 |
90.0 |
82.9 |
97.4 |
0.90 |
93.8 |
90.2 |
97.4 |
0.93 |
93.8 |
92.7 |
94.9 |
0.94 |
91.6 |
|
R. Forest |
87.5 |
87.8 |
87.2 |
0.96 |
92.5 |
90.2 |
94.9 |
0.97 |
91.5 |
87.8 |
94.9 |
0.97 |
88.8 |
85.4 |
92.3 |
0.94 |
91.5 |
|
KNN |
92.5 |
90.2 |
94.9 |
0.95 |
95.0 |
92.7 |
97.4 |
0.96 |
90.0 |
85.4 |
94.9 |
0.93 |
85.0 |
80.5 |
89.7 |
0.90 |
91.4 |
|
Logistic. R |
86.3 |
87.8 |
84.6 |
0.82 |
92.5 |
90.2 |
94.9 |
0.97 |
92.5 |
92.7 |
97.4 |
0.97 |
87.5 |
92.7 |
82.1 |
0.92 |
90.6 |
|
VFI |
87.5 |
82.9 |
92.3 |
0.95 |
92.5 |
90.2 |
94.9 |
0.97 |
88.8 |
85.4 |
92.3 |
0.95 |
87.5 |
82.9 |
92.3 |
0.92 |
90.5 |
|
Bayes Net |
91.3 |
90.2 |
92.3 |
0.97 |
90.0 |
85.4 |
94.9 |
0.98 |
90.0 |
85.4 |
94.9 |
0.95 |
83.8 |
78.0 |
89.7 |
0.89 |
90.3 |
|
MLP |
80.0 |
80.5 |
79.5 |
0.89 |
91.3 |
90.2 |
92.3 |
0.98 |
93.8 |
90.2 |
97.4 |
0.99 |
dnf |
dnf |
dnf |
dnf |
90.1* |
|
Hyper Pipes |
87.5 |
90.2 |
84.6 |
0.96 |
91.3 |
90.2 |
92.3 |
0.97 |
90.0 |
90.2 |
89.7 |
0.95 |
83.8 |
92.7 |
74.4 |
0.92 |
89.8 |
|
K-means |
91.3 |
82.9 |
100 |
0.92 |
90.0 |
82.9 |
97.4 |
0.90 |
86.3 |
78.0 |
94.9 |
0.87 |
85.0 |
75.6 |
94.9 |
0.85 |
88.3 |
|
M5P |
88.8 |
85.4 |
92.3 |
0.94 |
85.0 |
80.5 |
89.7 |
0.94 |
81.3 |
78.0 |
84.6 |
0.87 |
78.8 |
73.2 |
84.6 |
0.85 |
85.1 |
|
Random Tree |
85.0 |
87.8 |
82.1 |
0.85 |
78.8 |
75.6 |
82.1 |
0.79 |
87.5 |
85.4 |
89.7 |
0.88 |
83.8 |
85.4 |
82.1 |
0.84 |
83.8 |
|
K star |
87.5 |
87.8 |
87.2 |
0.96 |
91.3 |
85.4 |
97.4 |
0.98 |
90.0 |
85.4 |
94.9 |
0.97 |
53.8 |
100 |
5.1 |
0.54 |
81.9 |
|
J48 |
86.3 |
85.4 |
87.2 |
0.79 |
81.3 |
82.9 |
79.5 |
0.83 |
78.8 |
82.9 |
74.4 |
0.72 |
80.0 |
85.4 |
74.4 |
0.73 |
80.3 |
|
ASC |
86.3 |
85.4 |
87.2 |
0.79 |
80.0 |
82.9 |
76.9 |
0.80 |
80.0 |
87.8 |
71.8 |
0.78 |
66.3 |
80.5 |
51.3 |
0.55 |
76.8 |
| LDA | 88.8 | 82.9 | 94.9 | 0.96 | 91.3 | 85.4 | 97.4 | 0.95 | 40.0 | 96.7 | 15.8 | 0.68 | 21.3 | 94.4 | 0.0 | 0.48 | 69.7 |
Acc: Accuracy, Sp: Specificity, Sn: Sensitivity, AUC: Area under ROC curve, Avg: Average score in % for each algorithms, dnf: “Did Not Finish”, * denotes Avg. from 3 significance levels. Measures >90% are marked in bold.