RNA-seq Cancer Detection on Cervical Cancer RNA-seq Dataset
90AccuracyRGE-GCN
Evaluation Results
| Method | Links | |
|---|---|---|
| RGE-GCNClassifier=Graph Convolutional Network (GCN), #Genes=732025.12 | 90 | |
| limma-voomClassifier=Graph Convolutional Network (GCN), #Genes=582025.12 | 90 | |
| edgeRClassifier=Random Forest (RF), #Genes=582025.12 | 88.9 | |
| edgeRClassifier=Graph Convolutional Network (GCN), #Genes=582025.12 | 86.7 | |
| limma-voomClassifier=Random Forest (RF), #Genes=582025.12 | 86.7 | |
| RGE-GCNClassifier=Support Vector Machine (SVM), #Genes=732025.12 | 84.4 | |
| DESeq2Classifier=Random Forest (RF), #Genes=2022025.12 | 84.4 | |
| DESeq2Classifier=Graph Convolutional Network (GCN), #Genes=2022025.12 | 83.3 | |
| RGE-GCNClassifier=Random Forest (RF), #Genes=732025.12 | 80 | |
| edgeRClassifier=Support Vector Machine (SVM), #Genes=582025.12 | 78.9 | |
| DESeq2Classifier=Support Vector Machine (SVM), #Genes=2022025.12 | 76.7 | |
| edgeRClassifier=Multilayer Perceptron (MLP), #Genes=582025.12 | 76.7 | |
| limma-voomClassifier=Support Vector Machine (SVM), #Genes=582025.12 | 74.4 | |
| limma-voomClassifier=Multilayer Perceptron (MLP), #Genes=582025.12 | 73.3 | |
| DESeq2Classifier=Multilayer Perceptron (MLP), #Genes=2022025.12 | 70 | |
| RGE-GCNClassifier=Multilayer Perceptron (MLP), #Genes=732025.12 | 68.9 |