SMO Weka output to JSON
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=== Run information === Scheme: weka.classifiers.functions.SMO -C 1.0 -L 0.001 -P 1.0E-12 -N 0 -V -1 -W 1 -K "weka.classifiers.functions.supportVector.PolyKernel -E 2.0 -C 250007" -calibrator "weka.classifiers.functions.Logistic -R 1.0E-8 -M -1 -num-decimal-places 4" Relation: iris-weka.filters.unsupervised.attribute.Remove-R1-2 Instances: 150 Attributes: 3 petallength petalwidth class Test mode: 10-fold cross-validation === Classifier model (full training set) === SMO Kernel used: Poly Kernel: K(x,y) = <x,y>^2.0 Classifier for classes: Iris-setosa, Iris-versicolor BinarySMO - 1 * <0.118644 0.083333 > * X] + 1 * <0.491525 0.458333 > * X] + 1 * <0.457627 0.375 > * X] - 1 * <0.118644 0.166667 > * X] - 1 * <0.067797 0.083333 > * X] - 1 * <0.084746 0.125 > * X] + 1 * <0.338983 0.416667 > * X] + 1 * <0.389831 0.375 > * X] + 1 * <0.525424 0.375 > * X] - 1 * <0.084746 0.083333 > * X] + 1 * <0.491525 0.416667 > * X] + 1 * <0.423729 0.375 > * X] + 0.7401 * <0.508475 0.458333 > * X] - 1 * <0.067797 0.083333 > * X] - 1 * <0.152542 0.125 > * X] + 1 * <0.389831 0.375 > * X] + 1 * <0.440678 0.5 > * X] - 1 * <0.101695 0.208333 > * X] - 0.0811 * <0.067797 0.083333 > * X] - 0.5571 * <0.118644 0.041667 > * X] - 1 * <0.118644 0.125 > * X] - 0.5448 * <0.084746 0.125 > * X] + 1 * <0.474576 0.416667 > * X] - 0.0485 * <0.084746 0.125 > * X] - 0.7329 * <0.050847 0.125 > * X] - 1 * <0.101695 0.125 > * X] + 1 * <0.423729 0.375 > * X] - 0.7757 * <0.152542 0.041667 > * X] + 1 * <0.508475 0.375 > * X] - 1.1259 Number of support vectors: 29 Number of kernel evaluations: 3152 (70.807% cached) Classifier for classes: Iris-setosa, Iris-virginica BinarySMO 1 * <0.59322 0.666667 > * X] + 0.0594 * <0.779661 0.541667 > * X] - 1 * <0.152542 0.125 > * X] + 1 * <0.694915 0.583333 > * X] - 0.0594 * <0.118644 0.125 > * X] - 1 * <0.118644 0.166667 > * X] + 1 * <0.677966 0.583333 > * X] - 1 * <0.101695 0.208333 > * X] - 1.0689 Number of support vectors: 8 Number of kernel evaluations: 1249 (63.34% cached) Classifier for classes: Iris-versicolor, Iris-virginica BinarySMO 1 * <0.677966 0.75 > * X] - 1 * <0.59322 0.583333 > * X] - 1 * <0.627119 0.583333 > * X] - 1 * <0.59322 0.625 > * X] + 1 * <0.694915 0.708333 > * X] - 1 * <0.59322 0.583333 > * X] + 1 * <0.694915 0.75 > * X] - 1 * <0.694915 0.625 > * X] + 0.4998 * <0.779661 0.708333 > * X] - 1 * <0.677966 0.666667 > * X] - 1 * <0.627119 0.541667 > * X] + 1 * <0.762712 0.708333 > * X] - 1 * <0.627119 0.541667 > * X] + 1 * <0.728814 0.75 > * X] - 1 * <0.661017 0.583333 > * X] + 1 * <0.677966 0.583333 > * X] + 1 * <0.677966 0.791667 > * X] + 1 * <0.762712 0.708333 > * X] + 1 * <0.661017 0.708333 > * X] - 1 * <0.644068 0.541667 > * X] - 1 * <0.610169 0.541667 > * X] + 1 * <0.694915 0.75 > * X] + 1 * <0.644068 0.708333 > * X] - 1 * <0.644068 0.708333 > * X] + 1 * <0.779661 0.541667 > * X] + 1 * <0.661017 0.708333 > * X] + 1 * <0.661017 0.791667 > * X] - 1 * <0.661017 0.583333 > * X] - 0.4998 * <0.542373 0.583333 > * X] + 1 * <0.694915 0.583333 > * X] + 1 * <0.59322 0.666667 > * X] + 1 * <0.813559 0.625 > * X] - 1 * <0.627119 0.625 > * X] + 1 * <0.644068 0.708333 > * X] - 1 * <0.59322 0.583333 > * X] - 1 * <0.59322 0.583333 > * X] - 1 * <0.59322 0.583333 > * X] - 1 * <0.610169 0.583333 > * X] - 3.7642 Number of support vectors: 38 Number of kernel evaluations: 3463 (80.126% cached) Time taken to build model: 0.08 seconds === Stratified cross-validation === === Summary === Correctly Classified Instances 144 96 % Incorrectly Classified Instances 6 4 % Kappa statistic 0.94 Mean absolute error 0.2311 Root mean squared error 0.288 Relative absolute error 52 % Root relative squared error 61.101 % Total Number of Instances 150 === 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 Iris-setosa 0,960 0,040 0,923 0,960 0,941 0,911 0,960 0,899 Iris-versicolor 0,920 0,020 0,958 0,920 0,939 0,910 0,975 0,927 Iris-virginica Weighted Avg. 0,960 0,020 0,960 0,960 0,960 0,940 0,978 0,942 === Confusion Matrix === a b c <-- classified as 50 0 0 | a = Iris-setosa 0 48 2 | b = Iris-versicolor 0 4 46 | c = Iris-virginica
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