 | Run 26210 |
| Creator | internal |
| Program | sgd-logistic-stepsizeAdaGrad-iter5 |
| Dataset | dominionstats - large |
| Task type | MulticlassClassification |
| Created | 320d13h ago |
| Download | Login required! |
Done! 
| BinaryClassification | |
| 1m13s | |
| 0.368 | |
| 36s | |
| 0.368 | |
| 16s |
Log file
===== MAIN: learn based on training data =====
=== START program1: ./run learn ../dataset3/train
=== START program2: ./run learn ../program1/data
main() {
Reading examples from ../program1/data {
193657 examples, 520 features, 2 labels
} [25s, cum. 25s]
Iteration 0 {
numMistakes = 72606/193657 = 0.375
} [3.6s, cum. 28s]
Iteration 1 {
numMistakes = 72162/193657 = 0.373
} [6.2s, cum. 35s]
Iteration 2 {
numMistakes = 71247/193657 = 0.368
} [3.6s, cum. 38s]
Iteration 3 {
numMistakes = 70773/193657 = 0.365
} [3.7s, cum. 42s]
Iteration 4 {
numMistakes = 70055/193657 = 0.362
} [3.7s, cum. 46s]
Writing parameters to params
} [46s]
=== END program2: ./run learn ../program1/data --- OK [47s]
=== END program1: ./run learn ../dataset3/train --- OK [73s]
===== MAIN: predict/evaluate on train data =====
=== START program4: ./run stripLabels ../dataset3/train ../program0/evalTrain.in
=== END program4: ./run stripLabels ../dataset3/train ../program0/evalTrain.in --- OK [5s]
=== START program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out
=== START program2: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out.multiclass-output
main() {
Reading parameters from params
Reading examples from ../program0/evalTrain.in {
193657 examples, 520 features, 2 labels
} [24s, cum. 24s]
Predicting [3.5s, cum. 28s]
} [28s]
=== END program2: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out.multiclass-output --- OK [29s]
=== END program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out --- OK [36s]
=== START program5: ./run evaluate ../dataset3/train ../program0/evalTrain.out
=== END program5: ./run evaluate ../dataset3/train ../program0/evalTrain.out --- OK [20s]
===== MAIN: predict/evaluate on test data =====
=== START program4: ./run stripLabels ../dataset3/test ../program0/evalTest.in
=== END program4: ./run stripLabels ../dataset3/test ../program0/evalTest.in --- OK [3s]
=== START program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out
=== START program2: ./run predict ../program0/evalTest.in ../program0/evalTest.out.multiclass-output
main() {
Reading parameters from params
Reading examples from ../program0/evalTest.in {
82996 examples, 520 features, 2 labels
} [11s, cum. 11s]
Predicting
} [12s]
=== END program2: ./run predict ../program0/evalTest.in ../program0/evalTest.out.multiclass-output --- OK [13s]
=== END program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out --- OK [16s]
=== START program5: ./run evaluate ../dataset3/test ../program0/evalTest.out
=== END program5: ./run evaluate ../dataset3/test ../program0/evalTest.out --- OK [8s]
real 2m54.373s
user 2m27.253s
sys 0m12.949s
Run specification 
Results
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