Options: -C 0.25 -M 2 === Classifier model (full training set) === J48 pruned tree ------------------ 230387_at <= 7.839918 | 200037_s_at <= 12.225056: normal_homogenized (25.0) | 200037_s_at > 12.225056: tumoral_homogenized (18.0) 230387_at > 7.839918: tumoral_LCM (104.0) Number of Leaves : 3 Size of the tree : 5 Time taken to build model: 1.62 seconds Time taken to test model on training data: 1.86 seconds === Error on training data === Correctly Classified Instances 147 100 % Incorrectly Classified Instances 0 0 % Kappa statistic 1 Mean absolute error 0 Root mean squared error 0 Relative absolute error 0 % Root relative squared error 0 % Total Number of Instances 147 === 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 tumoral_LCM 1,000 0,000 1,000 1,000 1,000 1,000 1,000 1,000 normal_homogenized 1,000 0,000 1,000 1,000 1,000 1,000 1,000 1,000 tumoral_homogenized 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 104 0 0 | a = tumoral_LCM 0 25 0 | b = normal_homogenized 0 0 18 | c = tumoral_homogenized Time taken to perform cross-validation: 4.46 seconds === Stratified cross-validation === Correctly Classified Instances 132 89.7959 % Incorrectly Classified Instances 15 10.2041 % Kappa statistic 0.7893 Mean absolute error 0.068 Root mean squared error 0.2608 Relative absolute error 22.091 % Root relative squared error 66.9019 % Total Number of Instances 147 === Detailed Accuracy By Class === TP Rate FP Rate Precision Recall F-Measure MCC ROC Area PRC Area Class 0,923 0,023 0,990 0,923 0,955 0,864 0,950 0,968 tumoral_LCM 0,800 0,016 0,909 0,800 0,851 0,825 0,892 0,761 normal_homogenized 0,889 0,093 0,571 0,889 0,696 0,664 0,898 0,522 tumoral_homogenized Weighted Avg. 0,898 0,031 0,925 0,898 0,906 0,833 0,934 0,878 === Confusion Matrix === a b c <-- classified as 96 1 7 | a = tumoral_LCM 0 20 5 | b = normal_homogenized 1 1 16 | c = tumoral_homogenized