=== Classifier model (full training set) === ZeroR predicts class value: cancer_epithelial Time taken to build model: 0.01 seconds Time taken to test model on training data: 0.35 seconds === Error on training data === Correctly Classified Instances 28 42.4242 % Incorrectly Classified Instances 38 57.5758 % Kappa statistic 0 Mean absolute error 0.4128 Root mean squared error 0.4536 Relative absolute error 100 % Root relative squared error 100 % 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 1,000 0,424 1,000 0,596 ? 0,500 0,424 cancer_epithelial 0,000 0,000 ? 0,000 ? ? 0,500 0,424 cancer_stroma 0,000 0,000 ? 0,000 ? ? 0,500 0,152 normal Weighted Avg. 0,424 0,424 ? 0,424 ? ? 0,500 0,383 === Confusion Matrix === a b c <-- classified as 28 0 0 | a = cancer_epithelial 28 0 0 | b = cancer_stroma 10 0 0 | c = normal Time taken to perform cross-validation: 0.37 seconds === Stratified cross-validation === Correctly Classified Instances 27 40.9091 % Incorrectly Classified Instances 39 59.0909 % Kappa statistic -0.0263 Mean absolute error 0.4139 Root mean squared error 0.4542 Relative absolute error 100 % Root relative squared error 100 % Total Number of Instances 66 === Detailed Accuracy By Class === TP Rate FP Rate Precision Recall F-Measure MCC ROC Area PRC Area Class 0,643 0,684 0,409 0,643 0,500 -0,043 0,479 0,415 cancer_epithelial 0,321 0,342 0,409 0,321 0,360 -0,022 0,479 0,415 cancer_stroma 0,000 0,000 ? 0,000 ? ? 0,461 0,142 normal Weighted Avg. 0,409 0,435 ? 0,409 ? ? 0,477 0,373 === Confusion Matrix === a b c <-- classified as 18 10 0 | a = cancer_epithelial 19 9 0 | b = cancer_stroma 7 3 0 | c = normal