 | Run 7406 |
| Creator | jake |
| Program | svmlight_multiclass-linear |
| Dataset | simple-dataset |
| Task type | MulticlassClassification |
| Created | 1y122d ago |
| Download | Login required! |
Done! 
| 1s | |
| 0B | |
| MulticlassClassification | |
| 0 | |
| 0.500 | |
Log file
===== MAIN: learn based on training data ===== === START program1: ./run learn ../dataset2/train Using hyperparameter c = 0.1 Reading training examples... (4 examples) done Training set properties: 3 features, 2 classes Iter 1: ....*(NumConst=1, SV=1, CEps=100.0000, QPEps=0.0000) Iter 2: *(NumConst=2, SV=1, CEps=99.8625, QPEps=0.0000) Iter 3: ....(NumConst=2, SV=1, CEps=0.0000, QPEps=0.0000) Final epsilon on KKT-Conditions: 0.00000 Upper bound on duality gap: 0.00000 Dual objective value: dval=9.99312 Primal objective value: pval=9.99313 Total number of constraints in final working set: 2 (of 2) Number of iterations: 3 Number of calls to 'find_most_violated_constraint': 8 Number of SV: 1 Norm of weight vector: |w|=0.11726 Value of slack variable (on working set): xi=99.86250 Value of slack variable (global): xi=99.86250 Norm of longest difference vector: ||Psi(x,y)-Psi(x,ybar)||=1.17260 Runtime in cpu-seconds: 0.00 Final number of constraints in cache: 8 Compacting linear model...done Writing learned model...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...done. Reading test examples... (4 examples) done. Classifying test examples...done Runtime (without IO) in cpu-seconds: 0.00 Average loss on test set: 75.0000 Zero/one-error on test set: 75.00% (1 correct, 3 incorrect, 4 total) === 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 [0s] === START program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out Reading model...done. Reading test examples... (2 examples) done. Classifying test examples...done Runtime (without IO) in cpu-seconds: 0.00 Average loss on test set: 50.0000 Zero/one-error on test set: 50.00% (1 correct, 1 incorrect, 2 total) === 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 0m0.427s user 0m0.140s sys 0m0.080s
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