Table 1 Machine learning methods available in PCM-SABRE
Meta-node | Method | KNIME node | Default parameters | |
|---|---|---|---|---|
1.1 | Select patients | Estrogen Receptor status (ER) | R script | |
1.2 | Select patients | Lymph Node status (LN) | R script | |
2.1 | Feature Selection | Information Gain (InfoGain) | InformationGainCalculator (Community node – Palladian) | Top 100 ranked |
2.2 | Feature Selection | ANOVA | One-way ANOVA | include genes with p-value < 1.0E-6 |
3.1 | Modeling | Logistic Regression (LR) | Logistic (3.7) (Weka node) | Ridge = 1.0E-8, |
3.2 | Modeling | Random Forest (RF) | Random Forest Learner | Split criteria = Information Gain Ratio, Number of models = 350 |
3.3 | Modeling | Artificial Neural Network (ANN) | PNN Learner (DDA) | Theta Minus = 0.2, Theta Plus = 0.4 |
3.4 | Modeling | K-Nearest Neighbors (KNN) | IBK (3.7) (Weka node) | KNN = 15 |
3.5 | Modeling | Support Vector Machine (SVM) | SVM Learner | Kernel = RBF, sigma = 0.2 |