Benchopt
Dataset:
libsvm[dataset=rcv1.binary]
libsvm[dataset=news20.binary]
libsvm[dataset=gisette]
libsvm[dataset=colon-cancer]
Objective:
Sparse Logistic Regression[fit_intercept=False,reg=0.1]
Sparse Logistic Regression[fit_intercept=False,reg=0.01]
Sparse Logistic Regression[fit_intercept=False,reg=0.001]
Objective metrics
objective_value
Chart type
objective_curve
suboptimality_curve
relative_suboptimality_curve
bar_chart
Scale
semilog-y
semilog-x
loglog
linear
X-axis
Quantiles
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Dataset:
libsvm[dataset=rcv1.binary]
libsvm[dataset=news20.binary]
libsvm[dataset=gisette]
libsvm[dataset=colon-cancer]
Objective:
Sparse Logistic Regression[fit_intercept=False,reg=0.1]
Sparse Logistic Regression[fit_intercept=False,reg=0.01]
Sparse Logistic Regression[fit_intercept=False,reg=0.001]
Objective column
objective_value
Chart type
objective_curve
suboptimality_curve
relative_suboptimality_curve
bar_chart
Scale
semilog-y
semilog-x
loglog
linear
X-axis
Quantiles
Save as view
Result on logreg l1 benchmark
CPU : 10
RAM (GB) : 187
CUDA : Tesla V100-SXM2-16GB: cuda_11.4
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System information
CPU
: 10
RAM (GB)
: 187
CUDA
: Tesla V100-SXM2-16GB: cuda_11.4
platform
: Linux4.18.0-305.40.2.el8_4.x86_64-x86_64
processor
: Intel(R) Xeon(R) Gold 6248 CPU @ 2.50GHz
numpy
: 1.21.6 blas=NO_ATLAS_INFO lapack=lapack
scipy
: 1.8.1
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