1 |
Train Data Set |
-0.007 (0.7%) |
±0.344 (±34.3%) |
±0.688
(68.8%) |
2 |
Test Data Set |
-0.0830 (-8.3%) |
±0.203 (±20.3%) |
±0.406(±40.6%) |
3 |
Manual removing of test data with flow coefficient
\(C\leq 0.85\ \ \)or \(C\geq 1.15\) (as depicted in Fig. 12 (a)). |
-0.0588 (-5.9%) |
±0.073 (±7.3%) |
±0.146 (±14.6%) |
4 |
Filtering Test Data using Gaussian Naïve Bayes
algorithm with no calibration
|
-0.0945 (-9.5%) |
±0.080 (±8.0%) |
±0.161 (±16.1%) |
5 |
Filtering Test Data using Gaussian Naïve Bayes algorithm with
isotonic calibration |
-0.0928 (-9.3%) |
±0.124 (±12.4%) |
±0.247
(±24.7%) |
6 |
Filtering Test Data using Gaussian Naïve Bayes algorithm with
sigmoid calibration |
-0.0839 (-8.4%) |
±0.117 (±11.7%) |
±0.234
(±23.4%) |