 | Run 7759 |
| Creator | internal |
| Program | svmlight-linear |
| Dataset | sft2 |
| Task type | BinaryClassification |
| Created | 31d15h ago |
Done! 
| 1s | |
| 0B | |
| BinaryClassification | |
| 0s | |
| 0.089 | |
| 0s | |
| 0.077 | |
| 0s |
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..OK. (700 examples read) Setting default regularization parameter C=0.0043 Optimizing.......................................................................................................done. (104 iterations) Optimization finished (62 misclassified, maxdiff=0.00099). Runtime in cpu-seconds: 0.02 Number of SV: 131 (including 120 at upper bound) L1 loss: loss=124.01356 Norm of weight vector: |w|=0.00626 Norm of longest example vector: |x|=19.77739 Estimated VCdim of classifier: VCdim<=1.01534 Computing XiAlpha-estimates...done Runtime for XiAlpha-estimates in cpu-seconds: 0.00 XiAlpha-estimate of the error: error<=17.43% (rho=1.00,depth=0) XiAlpha-estimate of the recall: recall=>0.00% (rho=1.00,depth=0) XiAlpha-estimate of the precision: precision=>0.00% (rho=1.00,depth=0) Number of kernel evaluations: 8468 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. (131 support vectors read) Classifying test examples..100..200..300..400..500..600..700..done Runtime (without IO) in cpu-seconds: 0.00 === END program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out --- OK [0s] === 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 [1s] === START program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out Reading model...OK. (131 support vectors read) Classifying test examples..100..200..300..done Runtime (without IO) in cpu-seconds: 0.00 === END program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out --- OK [0s] === START program4: ./run evaluate ../dataset2/test ../program0/evalTest.out === END program4: ./run evaluate ../dataset2/test ../program0/evalTest.out --- OK [0s] real 0m0.946s user 0m0.348s sys 0m0.068s
Run specification 
Results
Must be logged in to post comments.