 | Run 14279 |
| Creator | internal |
| Program | svmlight-rbf |
| Dataset | Simple Bio-info Glycosylation Data |
| Task type | BinaryClassification |
| Created | 28d17h ago |
| Download | Login required! |
Done! 
| 2s | |
| 25M | |
| BinaryClassification | |
| 0s | |
| 0.172 | |
| 1s | |
| 0.134 | |
| 1s |
Log file
===== MAIN: learn based on training data ===== === START program1: ./run learn ../dataset2/train Scanning examples...done Reading examples into memory...100..200..300..400..OK. (400 examples read) Setting default regularization parameter C=0.5000 Optimizing...................................................................................................................................................................................................done. (196 iterations) Optimization finished (69 misclassified, maxdiff=0.00089). Runtime in cpu-seconds: 0.15 Number of SV: 400 (including 69 at upper bound) L1 loss: loss=96.31595 Norm of weight vector: |w|=4.56574 Norm of longest example vector: |x|=1.00000 Estimated VCdim of classifier: VCdim<=42.69197 Computing XiAlpha-estimates...done Runtime for XiAlpha-estimates in cpu-seconds: 0.00 XiAlpha-estimate of the error: error<=17.25% (rho=1.00,depth=0) XiAlpha-estimate of the recall: recall=>100.00% (rho=1.00,depth=0) XiAlpha-estimate of the precision: precision=>82.75% (rho=1.00,depth=0) Number of kernel evaluations: 96125 Writing model file...done === END program1: ./run learn ../dataset2/train --- OK [0s] ===== MAIN: predict/evaluate on train data ===== === START program3: ./run stripLabels ../dataset2/train ../program0/evalTrain.in === END program3: ./run stripLabels ../dataset2/train ../program0/evalTrain.in --- OK [0s] === START program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out Reading model...OK. (400 support vectors read) Classifying test examples..100..200..300..400..done Runtime (without IO) in cpu-seconds: 0.24 === END program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out --- OK [1s] === START program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out === END program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out --- OK [0s] ===== MAIN: predict/evaluate on test data ===== === START program3: ./run stripLabels ../dataset2/test ../program0/evalTest.in === END program3: ./run stripLabels ../dataset2/test ../program0/evalTest.in --- OK [0s] === START program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out Reading model...OK. (400 support vectors read) Classifying test examples..100..done Runtime (without IO) in cpu-seconds: 0.12 === END program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out --- OK [1s] === START program4: ./run evaluate ../dataset2/test ../program0/evalTest.out === END program4: ./run evaluate ../dataset2/test ../program0/evalTest.out --- OK [0s] real 0m2.532s user 0m1.728s sys 0m0.556s
Run specification 
Results
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