Options: -K 1 -W 0 -A "weka.core.neighboursearch.LinearNNSearch -A "weka.core.EuclideanDistance -R first-last"" === Classifier model (full training set) === IB1 instance-based classifier using 1 nearest neighbour(s) for classification Time taken to build model: 1.02 seconds Time taken to test model on training data: 1.07 seconds === Error on training data === Correctly Classified Instances 66 100 % Incorrectly Classified Instances 0 0 % Kappa statistic 1 Mean absolute error 0.0193 Root mean squared error 0.0205 Relative absolute error 4.6809 % Root relative squared error 4.5188 % 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: 1.35 seconds === Stratified cross-validation === Correctly Classified Instances 36 54.5455 % Incorrectly Classified Instances 30 45.4545 % Kappa statistic 0.2964 Mean absolute error 0.3121 Root mean squared error 0.5335 Relative absolute error 75.3894 % Root relative squared error 117.4552 % Total Number of Instances 66 === Detailed Accuracy By Class === TP Rate FP Rate Precision Recall F-Measure MCC ROC Area PRC Area Class 0,464 0,289 0,542 0,464 0,500 0,180 0,587 0,479 cancer_epithelial 0,571 0,237 0,640 0,571 0,604 0,341 0,667 0,548 cancer_stroma 0,700 0,179 0,412 0,700 0,519 0,428 0,761 0,334 normal Weighted Avg. 0,545 0,250 0,564 0,545 0,547 0,286 0,648 0,486 === Confusion Matrix === a b c <-- classified as 13 7 8 | a = cancer_epithelial 10 16 2 | b = cancer_stroma 1 2 7 | c = normal