ServerRun 43150
CreatorHossein
Programliblinear-s6-B1
DatasetCancer
Task typeBinaryClassification
Created1y70d ago
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11s
50M
BinaryClassification
0s
0.337
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0.374
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Log file

g++ -Wall -Wconversion -O3 -fPIC -c -o tron.o tron.cpp
g++ -Wall -Wconversion -O3 -fPIC -c -o linear.o linear.cpp
linear.cpp: In function ‘model* load_model(const char*)’:
linear.cpp:1832:24: warning: ignoring return value of ‘int fscanf(FILE*, const char*, ...)’, declared with attribute warn_unused_result
linear.cpp:1835:25: warning: ignoring return value of ‘int fscanf(FILE*, const char*, ...)’, declared with attribute warn_unused_result
linear.cpp:1855:29: warning: ignoring return value of ‘int fscanf(FILE*, const char*, ...)’, declared with attribute warn_unused_result
linear.cpp:1860:31: warning: ignoring return value of ‘int fscanf(FILE*, const char*, ...)’, declared with attribute warn_unused_result
linear.cpp:1865:26: warning: ignoring return value of ‘int fscanf(FILE*, const char*, ...)’, declared with attribute warn_unused_result
linear.cpp:1877:38: warning: ignoring return value of ‘int fscanf(FILE*, const char*, ...)’, declared with attribute warn_unused_result
linear.cpp:1904:44: warning: ignoring return value of ‘int fscanf(FILE*, const char*, ...)’, declared with attribute warn_unused_result
linear.cpp:1905:19: warning: ignoring return value of ‘int fscanf(FILE*, const char*, ...)’, declared with attribute warn_unused_result
linear.cpp: In function ‘void train_one(const problem*, const parameter*, double*, double, double)’:
linear.cpp:918:9: warning: ‘loss_old’ may be used uninitialized in this function
linear.cpp:916:9: warning: ‘Gmax_init’ may be used uninitialized in this function
linear.cpp:1196:9: warning: ‘Gmax_init’ may be used uninitialized in this function
cd blas; make OPTFLAGS='-Wall -Wconversion -O3 -fPIC' CC='cc';
make[1]: Entering directory `/home/mlcomp/worker/scratch/program1/liblinear-1.51/blas'
cc -Wall -Wconversion -O3 -fPIC  -c dnrm2.c
cc -Wall -Wconversion -O3 -fPIC  -c daxpy.c
cc -Wall -Wconversion -O3 -fPIC  -c ddot.c
cc -Wall -Wconversion -O3 -fPIC  -c dscal.c
ar rcv blas.a dnrm2.o daxpy.o ddot.o dscal.o   
a - dnrm2.o
a - daxpy.o
a - ddot.o
a - dscal.o
ranlib  blas.a
make[1]: Leaving directory `/home/mlcomp/worker/scratch/program1/liblinear-1.51/blas'
g++ -Wall -Wconversion -O3 -fPIC -o train train.c tron.o linear.o blas/blas.a
g++ -Wall -Wconversion -O3 -fPIC -o predict predict.c tron.o linear.o blas/blas.a
===== MAIN: learn based on training data =====
=== START program1: ./run learn ../dataset2/train
...**
optimization finished, #iter = 35
Objective value = 319.118215
#nonzeros/#features = 16/17
=== 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
Accuracy = 23.0174% (119/517)
=== 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
Accuracy = 20.2703% (45/222)
=== 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	0m12.004s
user	0m4.812s
sys	0m1.100s

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