 | Run 11533 |
| Creator | rhnet |
| Program | svmlight-rbf |
| Dataset | fidofetch_newlines |
| Task type | BinaryClassification |
| Created | 28d16h ago |
Done! 
| 4s | |
| 68M | |
| BinaryClassification | |
| 2s | |
| 0.454 | |
| 2s | |
| 0.514 | |
| 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..500..600..700..800..900..1000..OK. (1058 examples read) Setting default regularization parameter C=0.5029 Optimizing................................................................................................................................................................................................................................................................................................................ Checking optimality of inactive variables...done. Number of inactive variables = 504 done. (305 iterations) Optimization finished (480 misclassified, maxdiff=0.00090). Runtime in cpu-seconds: 0.44 Number of SV: 1047 (including 516 at upper bound) L1 loss: loss=506.99000 Norm of weight vector: |w|=16.14625 Norm of longest example vector: |x|=1.00000 Estimated VCdim of classifier: VCdim<=522.40257 Computing XiAlpha-estimates...done Runtime for XiAlpha-estimates in cpu-seconds: 0.00 XiAlpha-estimate of the error: error<=48.77% (rho=1.00,depth=0) XiAlpha-estimate of the recall: recall=>98.88% (rho=1.00,depth=0) XiAlpha-estimate of the precision: precision=>50.96% (rho=1.00,depth=0) Number of kernel evaluations: 590624 Writing model file...done === END program1: ./run learn ../dataset2/train --- OK [2s] ===== 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. (1047 support vectors read) Classifying test examples..100..200..300..400..500..600..700..800..900..1000..done Runtime (without IO) in cpu-seconds: 0.65 === END program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out --- OK [2s] === 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. (1047 support vectors read) Classifying test examples..100..200..300..400..done Runtime (without IO) in cpu-seconds: 0.29 === 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 0m5.911s user 0m1.876s sys 0m0.084s
Run specification 
Results
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