Multi-class Classification on Pageblocks
97.34F1-scoreIMOVNO+
Evaluation results
| Method | Links | |||||
|---|---|---|---|---|---|---|
| IMOVNO+Validation=5-fold cross-validation2026.02 | 97.34 | 97.63 | 97.34 | 97.22 | — | |
| IMOVNO+Binarization=true, Cross-validation=5-fold2026.02 | 97.34 | 97.63 | 97.34 | 97.22 | — | |
| IMOVNO+Evaluation Protocol=5-fold cross-validation2026.02 | 97.34 | — | — | 97.22 | 97.34 | |
| IMOVNO+Strategy=Binarization, Validation=5-fold cross-validation2026.02 | 97.34 | 97.63 | 97.34 | 97.22 | — | |
| OVO-ISMOTEBinarization=true, Cross-validation=5-fold2026.02 | 76.01 | 70.46 | 78.64 | 57.13 | — | |
| OVO-ISMOTEStrategy=Binarization, Validation=5-fold cross-validation2026.02 | 76.01 | 70.46 | 78.64 | 57.13 | — | |
| OVO-HSCFBinarization=true, Cross-validation=5-fold2026.02 | 72.01 | 75.31 | 72.41 | 45.88 | — | |
| OVO-HSCFStrategy=Binarization, Validation=5-fold cross-validation2026.02 | 72.01 | 75.31 | 72.41 | 45.88 | — | |
| SVM-E-EVRSEvaluation Protocol=5-fold cross-validation2026.02 | 70.2 | — | — | 59.2 | — | |
| DT-E-EVRSEvaluation Protocol=5-fold cross-validation2026.02 | 70 | — | — | 55.8 | — | |
| SMOTE-CDNNValidation=5-fold cross-validation2026.02 | 64.3 | 59.63 | 78.56 | 49.57 | — | |
| SAMME.C2Validation=5-fold cross-validation2026.02 | 62.54 | 65.52 | 63.84 | 26.63 | — | |
| ECDNNValidation=5-fold cross-validation2026.02 | 43.25 | 48.53 | 41.17 | 5.74 | — | |
| OVO-GDDSADBinarization=true, Cross-validation=5-fold2026.02 | 36.44 | 34.67 | 52.49 | 25.36 | — | |
| OVO-GDDSADStrategy=Binarization, Validation=5-fold cross-validation2026.02 | 36.44 | 34.67 | 52.49 | 25.36 | — | |
| FAMeXClassifier=Naive Bayes, Feature Importance Subset=Top 30%2026.05 | — | — | — | — | 94.08 | |
| FAMeXClassifier=Naive Bayes, Feature Importance Subset=Bottom 30%2026.05 | — | — | — | — | 92.97 | |
| PFIClassifier=Naive Bayes, Feature Importance Subset=Top 30%2026.05 | — | — | — | — | 78.21 | |
| PFIClassifier=Naive Bayes, Feature Importance Subset=Bottom 30%2026.05 | — | — | — | — | 78.35 | |
| SHAPClassifier=Naive Bayes, Feature Importance Subset=Top 30%2026.05 | — | — | — | — | 87.5 | |
| SHAPClassifier=Naive Bayes, Feature Importance Subset=Bottom 30%2026.05 | — | — | — | — | 90.45 |