Options: -P 100 -I 100 -num-slots 1 -K 0 -M 1.0 -V 0.001 -S 1 === Classifier model (full training set) === RandomForest Bagging with 100 iterations and base learner weka.classifiers.trees.RandomTree -K 0 -M 1.0 -V 0.001 -S 1 -do-not-check-capabilities Time taken to build model: 1.91 seconds Time taken to test model on training data: 0.37 seconds === Error on training data === Correctly Classified Instances 66 100 % Incorrectly Classified Instances 0 0 % Kappa statistic 1 Mean absolute error 0.1236 Root mean squared error 0.1477 Relative absolute error 29.9489 % Root relative squared error 32.5737 % Total Number of Instances 66 === Detailed Accuracy By Class === TP Rate FP Rate Precision Recall F-Measure MCC ROC Area PRC Area Class 1,000 0,000 1,000 1,000 1,000 1,000 1,000 1,000 cancer_epithelial 1,000 0,000 1,000 1,000 1,000 1,000 1,000 1,000 cancer_stroma 1,000 0,000 1,000 1,000 1,000 1,000 1,000 1,000 normal Weighted Avg. 1,000 0,000 1,000 1,000 1,000 1,000 1,000 1,000 === Confusion Matrix === a b c <-- classified as 28 0 0 | a = cancer_epithelial 0 28 0 | b = cancer_stroma 0 0 10 | c = normal Time taken to perform cross-validation: 5.5 seconds === Stratified cross-validation === Correctly Classified Instances 43 65.1515 % Incorrectly Classified Instances 23 34.8485 % Kappa statistic 0.3947 Mean absolute error 0.3332 Root mean squared error 0.3914 Relative absolute error 80.5052 % Root relative squared error 86.168 % Total Number of Instances 66 === Detailed Accuracy By Class === TP Rate FP Rate Precision Recall F-Measure MCC ROC Area PRC Area Class 0,786 0,342 0,629 0,786 0,698 0,439 0,835 0,837 cancer_epithelial 0,750 0,263 0,677 0,750 0,712 0,482 0,822 0,703 cancer_stroma 0,000 0,000 ? 0,000 ? ? 0,783 0,661 normal Weighted Avg. 0,652 0,257 ? 0,652 ? ? 0,822 0,754 === Confusion Matrix === a b c <-- classified as 22 6 0 | a = cancer_epithelial 7 21 0 | b = cancer_stroma 6 4 0 | c = normal