Note
Go to the end to download the full example code.
Illustration of additional features of Biogeme
- Same model as b01logit, using bioLinearUtility, segmentations
and features.
- author:
Michel Bierlaire, EPFL
- date:
Sun Apr 9 17:03:31 2023
import biogeme.biogeme as bio
import biogeme.biogeme_logging as blog
import biogeme.segmentation as seg
from biogeme import models
from biogeme.expressions import Beta, bioLinearUtility, LinearTermTuple
logger = blog.get_screen_logger(level=blog.INFO)
logger.info('Example b01logit.py')
Example b01logit.py
See the data processing script: Data preparation for Swissmetro.
from swissmetro_data import (
database,
CHOICE,
GA,
CAR_AV_SP,
TRAIN_AV_SP,
TRAIN_TT_SCALED,
TRAIN_COST_SCALED,
SM_TT_SCALED,
SM_COST_SCALED,
CAR_TT_SCALED,
CAR_CO_SCALED,
MALE,
SM_AV,
)
logger = blog.get_screen_logger(level=blog.INFO)
logger.info('Example b01logit_bis.py')
Example b01logit_bis.py
Example b01logit_bis.py
Parameters to be estimated.
ASC_CAR = Beta('ASC_CAR', 0, None, None, 0)
ASC_TRAIN = Beta('ASC_TRAIN', 0, None, None, 0)
Starting value. We use starting values estimated from a previous run
B_TIME = Beta('B_TIME', -1.28, None, None, 0)
B_COST = Beta('B_COST', -1.08, None, None, 0)
Define segmentations.
gender_segmentation = database.generate_segmentation(
variable=MALE, mapping={0: 'female', 1: 'male'}
)
GA_segmentation = database.generate_segmentation(
variable=GA, mapping={0: 'without_ga', 1: 'with_ga'}
)
segmentations_for_asc = [
gender_segmentation,
GA_segmentation,
]
Segmentation of the constants.
ASC_TRAIN_segmentation = seg.Segmentation(ASC_TRAIN, segmentations_for_asc)
segmented_ASC_TRAIN = ASC_TRAIN_segmentation.segmented_beta()
ASC_CAR_segmentation = seg.Segmentation(ASC_CAR, segmentations_for_asc)
segmented_ASC_CAR = ASC_CAR_segmentation.segmented_beta()
Definition of the utility functions.
terms1 = [
LinearTermTuple(beta=B_TIME, x=TRAIN_TT_SCALED),
LinearTermTuple(beta=B_COST, x=TRAIN_COST_SCALED),
]
V1 = segmented_ASC_TRAIN + bioLinearUtility(terms1)
terms2 = [
LinearTermTuple(beta=B_TIME, x=SM_TT_SCALED),
LinearTermTuple(beta=B_COST, x=SM_COST_SCALED),
]
V2 = bioLinearUtility(terms2)
terms3 = [
LinearTermTuple(beta=B_TIME, x=CAR_TT_SCALED),
LinearTermTuple(beta=B_COST, x=CAR_CO_SCALED),
]
V3 = segmented_ASC_CAR + bioLinearUtility(terms3)
Associate utility functions with the numbering of alternatives.
V = {1: V1, 2: V2, 3: V3}
Associate the availability conditions with the alternatives.
av = {1: TRAIN_AV_SP, 2: SM_AV, 3: CAR_AV_SP}
Definition of the model.
This is the contribution of each observation to the log likelihood function.
logprob = models.loglogit(V, av, CHOICE)
User notes.
These notes will be included as such in the report file.
USER_NOTES = (
'Example of a logit model with three alternatives: Train, Car and'
' Swissmetro. Same as 01logit and '
'introducing some options and features. In particular, bioLinearUtility,'
' and automatic segmentation of parameters.'
)
Create the Biogeme object. We include users notes, and we ask not to calculate the second derivatives.
the_biogeme = bio.BIOGEME(
database, logprob, user_notes=USER_NOTES, second_derivatives=0
)
Biogeme parameters read from biogeme.toml.
Biogeme parameters read from biogeme.toml.
Calculate the null log likelihood for reporting.
As we have used starting values different from 0, the initial model is not the equal probability model.
the_biogeme.calculate_null_loglikelihood(av)
the_biogeme.modelName = 'b01logit_bis'
Turn off saving iterations.
the_biogeme.save_iterations = False
Estimate the parameters.
the_biogeme.bootstrap_samples = 100
results = the_biogeme.estimate(run_bootstrap=True)
As the model is not too complex, we activate the calculation of second derivatives. If you want to change it, change the name of the algorithm in the TOML file from "automatic" to "simple_bounds"
As the model is not too complex, we activate the calculation of second derivatives. If you want to change it, change the name of the algorithm in the TOML file from "automatic" to "simple_bounds"
As the model is not too complex, we activate the calculation of second derivatives. If you want to change it, change the name of the algorithm in the TOML file from "automatic" to "simple_bounds"
As the model is not too complex, we activate the calculation of second derivatives. If you want to change it, change the name of the algorithm in the TOML file from "automatic" to "simple_bounds"
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.38 -0.046 -0.2 -0.21 -0.78 1 -1 -1.3 5.1e+03 0.053 10 1.1 ++
0 -0.38 -0.046 -0.2 -0.21 -0.78 1 -1 -1.3 5.1e+03 0.053 10 1.1 ++
1 -0.61 0.42 -0.42 -0.53 -1 1.8 -1.1 -1.1 4.9e+03 0.0091 1e+02 1 ++
1 -0.61 0.42 -0.42 -0.53 -1 1.8 -1.1 -1.1 4.9e+03 0.0091 1e+02 1 ++
2 -0.61 0.41 -0.41 -0.53 -1.1 1.9 -1.1 -1.2 4.9e+03 0.00031 1e+03 1 ++
2 -0.61 0.41 -0.41 -0.53 -1.1 1.9 -1.1 -1.2 4.9e+03 0.00031 1e+03 1 ++
3 -0.61 0.41 -0.41 -0.53 -1.1 1.9 -1.1 -1.2 4.9e+03 6.6e-07 1e+03 1 ++
3 -0.61 0.41 -0.41 -0.53 -1.1 1.9 -1.1 -1.2 4.9e+03 6.6e-07 1e+03 1 ++
Re-estimate the model 100 times for bootstrapping
Re-estimate the model 100 times for bootstrapping
0%| | 0/100 [00:00<?, ?it/s]Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.52 0.3 -0.08 -0.56 -1.1 2 -1.1 -1.2 5e+03 0.00026 10 0.96 ++
0 -0.52 0.3 -0.08 -0.56 -1.1 2 -1.1 -1.2 5e+03 0.00026 10 0.96 ++
1 -0.52 0.3 -0.08 -0.56 -1.1 2 -1.1 -1.2 5e+03 2.1e-06 10 1 ++
1 -0.52 0.3 -0.08 -0.56 -1.1 2 -1.1 -1.2 5e+03 2.1e-06 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.59 0.5 -0.51 -0.48 -0.94 1.8 -1.2 -1.4 4.9e+03 0.00073 10 1 ++
0 -0.59 0.5 -0.51 -0.48 -0.94 1.8 -1.2 -1.4 4.9e+03 0.00073 10 1 ++
1 -0.59 0.5 -0.51 -0.48 -0.94 1.8 -1.2 -1.4 4.9e+03 1.9e-06 10 1 ++
1 -0.59 0.5 -0.51 -0.48 -0.94 1.8 -1.2 -1.4 4.9e+03 1.9e-06 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.57 0.41 -0.52 -0.55 -1.2 2 -0.94 -1.2 4.9e+03 0.00056 10 1 ++
0 -0.57 0.41 -0.52 -0.55 -1.2 2 -0.94 -1.2 4.9e+03 0.00056 10 1 ++
1 -0.57 0.41 -0.52 -0.55 -1.2 2 -0.94 -1.2 4.9e+03 2.1e-06 10 1 ++
1 -0.57 0.41 -0.52 -0.55 -1.2 2 -0.94 -1.2 4.9e+03 2.1e-06 10 1 ++
3%|▎ | 3/100 [00:00<00:04, 20.60it/s]Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.58 0.38 -0.062 -0.49 -1.1 1.9 -1.1 -1.2 5e+03 0.00036 10 0.92 ++
0 -0.58 0.38 -0.062 -0.49 -1.1 1.9 -1.1 -1.2 5e+03 0.00036 10 0.92 ++
1 -0.58 0.38 -0.062 -0.49 -1.1 1.9 -1.1 -1.2 5e+03 5.2e-06 10 1 ++
1 -0.58 0.38 -0.062 -0.49 -1.1 1.9 -1.1 -1.2 5e+03 5.2e-06 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.86 0.62 -0.56 -0.53 -1.2 2 -1.1 -1.2 4.9e+03 0.00051 10 1 ++
0 -0.86 0.62 -0.56 -0.53 -1.2 2 -1.1 -1.2 4.9e+03 0.00051 10 1 ++
1 -0.86 0.62 -0.56 -0.53 -1.2 2 -1.1 -1.2 4.9e+03 3.5e-06 10 1 ++
1 -0.86 0.62 -0.56 -0.53 -1.2 2 -1.1 -1.2 4.9e+03 3.5e-06 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.48 0.26 -0.31 -0.64 -0.97 1.8 -1 -1.2 5e+03 0.00021 10 0.99 ++
0 -0.48 0.26 -0.31 -0.64 -0.97 1.8 -1 -1.2 5e+03 0.00021 10 0.99 ++
1 -0.48 0.26 -0.31 -0.64 -0.97 1.8 -1 -1.2 5e+03 6.7e-07 10 1 ++
1 -0.48 0.26 -0.31 -0.64 -0.97 1.8 -1 -1.2 5e+03 6.7e-07 10 1 ++
6%|▌ | 6/100 [00:00<00:04, 20.77it/s]Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.74 0.51 -0.55 -0.64 -1 1.9 -1.1 -1.2 4.9e+03 0.00013 10 1 ++
0 -0.74 0.51 -0.55 -0.64 -1 1.9 -1.1 -1.2 4.9e+03 0.00013 10 1 ++
1 -0.74 0.51 -0.55 -0.64 -1 1.9 -1.1 -1.2 4.9e+03 3.9e-07 10 1 ++
1 -0.74 0.51 -0.55 -0.64 -1 1.9 -1.1 -1.2 4.9e+03 3.9e-07 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.71 0.61 -0.73 -0.43 -1.1 2 -1 -1.4 4.8e+03 0.002 10 1 ++
0 -0.71 0.61 -0.73 -0.43 -1.1 2 -1 -1.4 4.8e+03 0.002 10 1 ++
1 -0.71 0.61 -0.73 -0.43 -1.1 2 -1 -1.4 4.8e+03 1e-05 10 1 ++
1 -0.71 0.61 -0.73 -0.43 -1.1 2 -1 -1.4 4.8e+03 1e-05 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.55 0.29 -0.41 -0.62 -1.1 1.9 -1 -1 5e+03 0.00065 10 0.97 ++
0 -0.55 0.29 -0.41 -0.62 -1.1 1.9 -1 -1 5e+03 0.00065 10 0.97 ++
1 -0.55 0.29 -0.41 -0.62 -1.1 1.9 -1 -1 5e+03 1.7e-06 10 1 ++
1 -0.55 0.29 -0.41 -0.62 -1.1 1.9 -1 -1 5e+03 1.7e-06 10 1 ++
9%|▉ | 9/100 [00:00<00:04, 20.79it/s]Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.66 0.52 -0.44 -0.48 -1 1.7 -1 -1.2 5e+03 0.00016 10 1 ++
0 -0.66 0.52 -0.44 -0.48 -1 1.7 -1 -1.2 5e+03 0.00016 10 1 ++
1 -0.66 0.52 -0.44 -0.48 -1 1.7 -1 -1.2 5e+03 1.2e-07 10 1 ++
1 -0.66 0.52 -0.44 -0.48 -1 1.7 -1 -1.2 5e+03 1.2e-07 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.66 0.48 -0.59 -0.53 -0.99 1.8 -1 -1.1 5e+03 0.00043 10 0.98 ++
0 -0.66 0.48 -0.59 -0.53 -0.99 1.8 -1 -1.1 5e+03 0.00043 10 0.98 ++
1 -0.66 0.48 -0.59 -0.53 -0.99 1.8 -1 -1.1 5e+03 1e-06 10 1 ++
1 -0.66 0.48 -0.59 -0.53 -0.99 1.8 -1 -1.1 5e+03 1e-06 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.57 0.4 -0.62 -0.52 -1.2 1.9 -1 -1.2 4.9e+03 0.00028 10 1 ++
0 -0.57 0.4 -0.62 -0.52 -1.2 1.9 -1 -1.2 4.9e+03 0.00028 10 1 ++
1 -0.57 0.4 -0.62 -0.52 -1.2 1.9 -1 -1.2 4.9e+03 4.8e-07 10 1 ++
1 -0.57 0.4 -0.62 -0.52 -1.2 1.9 -1 -1.2 4.9e+03 4.8e-07 10 1 ++
12%|█▏ | 12/100 [00:00<00:04, 20.68it/s]Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.71 0.46 -0.07 -0.6 -1.1 1.9 -1.2 -1.1 5e+03 0.00042 10 0.99 ++
0 -0.71 0.46 -0.07 -0.6 -1.1 1.9 -1.2 -1.1 5e+03 0.00042 10 0.99 ++
1 -0.71 0.46 -0.07 -0.6 -1.1 1.9 -1.2 -1.1 5e+03 1.3e-06 10 1 ++
1 -0.71 0.46 -0.07 -0.6 -1.1 1.9 -1.2 -1.1 5e+03 1.3e-06 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.64 0.46 -0.53 -0.46 -1.1 1.8 -1.1 -1.3 4.8e+03 0.00073 10 1 ++
0 -0.64 0.46 -0.53 -0.46 -1.1 1.8 -1.1 -1.3 4.8e+03 0.00073 10 1 ++
1 -0.64 0.46 -0.53 -0.46 -1.1 1.8 -1.1 -1.3 4.8e+03 1.3e-06 10 1 ++
1 -0.64 0.46 -0.53 -0.46 -1.1 1.8 -1.1 -1.3 4.8e+03 1.3e-06 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.77 0.59 -0.43 -0.62 -0.91 1.9 -1.1 -1.2 5e+03 0.00026 10 0.99 ++
0 -0.77 0.59 -0.43 -0.62 -0.91 1.9 -1.1 -1.2 5e+03 0.00026 10 0.99 ++
1 -0.77 0.59 -0.43 -0.62 -0.91 1.9 -1.1 -1.2 5e+03 3.4e-07 10 1 ++
1 -0.77 0.59 -0.43 -0.62 -0.91 1.9 -1.1 -1.2 5e+03 3.4e-07 10 1 ++
15%|█▌ | 15/100 [00:00<00:04, 20.61it/s]Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.73 0.47 -0.12 -0.72 -1 2.1 -1.1 -1.1 5e+03 0.0003 10 0.99 ++
0 -0.73 0.47 -0.12 -0.72 -1 2.1 -1.1 -1.1 5e+03 0.0003 10 0.99 ++
1 -0.73 0.47 -0.12 -0.72 -1 2.1 -1.1 -1.1 5e+03 6.5e-07 10 1 ++
1 -0.73 0.47 -0.12 -0.72 -1 2.1 -1.1 -1.1 5e+03 6.5e-07 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.57 0.4 -0.35 -0.52 -0.98 1.9 -1.1 -1.3 4.9e+03 0.00033 10 1 ++
0 -0.57 0.4 -0.35 -0.52 -0.98 1.9 -1.1 -1.3 4.9e+03 0.00033 10 1 ++
1 -0.57 0.4 -0.35 -0.52 -0.98 1.9 -1.1 -1.3 4.9e+03 2.4e-07 10 1 ++
1 -0.57 0.4 -0.35 -0.52 -0.98 1.9 -1.1 -1.3 4.9e+03 2.4e-07 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.65 0.34 -0.29 -0.63 -1.1 2.1 -1.1 -1.2 4.8e+03 0.00022 10 1 ++
0 -0.65 0.34 -0.29 -0.63 -1.1 2.1 -1.1 -1.2 4.8e+03 0.00022 10 1 ++
1 -0.65 0.34 -0.29 -0.63 -1.1 2.1 -1.1 -1.2 4.8e+03 1.3e-07 10 1 ++
1 -0.65 0.34 -0.29 -0.63 -1.1 2.1 -1.1 -1.2 4.8e+03 1.3e-07 10 1 ++
18%|█▊ | 18/100 [00:00<00:03, 20.53it/s]Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.75 0.58 -0.81 -0.58 -1 1.8 -0.97 -1.1 5e+03 0.00054 10 0.99 ++
0 -0.75 0.58 -0.81 -0.58 -1 1.8 -0.97 -1.1 5e+03 0.00054 10 0.99 ++
1 -0.75 0.58 -0.81 -0.58 -1 1.8 -0.97 -1.1 5e+03 4.2e-06 10 1 ++
1 -0.75 0.58 -0.81 -0.58 -1 1.8 -0.97 -1.1 5e+03 4.2e-06 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.61 0.41 -0.41 -0.53 -1.1 1.9 -1.1 -1.2 5e+03 0.00011 1 1
0 -0.61 0.41 -0.41 -0.53 -1.1 1.9 -1.1 -1.2 5e+03 0.00011 1 1
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.64 0.49 -0.22 -0.55 -1.1 1.9 -1.1 -1.2 4.9e+03 0.00014 10 0.98 ++
0 -0.64 0.49 -0.22 -0.55 -1.1 1.9 -1.1 -1.2 4.9e+03 0.00014 10 0.98 ++
1 -0.64 0.49 -0.22 -0.55 -1.1 1.9 -1.1 -1.2 4.9e+03 6.8e-07 10 1 ++
1 -0.64 0.49 -0.22 -0.55 -1.1 1.9 -1.1 -1.2 4.9e+03 6.8e-07 10 1 ++
21%|██ | 21/100 [00:01<00:03, 21.17it/s]Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.57 0.39 -0.22 -0.61 -0.96 1.9 -1.1 -1.1 5e+03 0.00028 10 0.98 ++
0 -0.57 0.39 -0.22 -0.61 -0.96 1.9 -1.1 -1.1 5e+03 0.00028 10 0.98 ++
1 -0.57 0.39 -0.22 -0.61 -0.96 1.9 -1.1 -1.1 5e+03 9e-07 10 1 ++
1 -0.57 0.39 -0.22 -0.61 -0.96 1.9 -1.1 -1.1 5e+03 9e-07 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.51 0.26 -0.33 -0.6 -1.1 2.1 -0.95 -1.1 5e+03 0.00043 10 0.98 ++
0 -0.51 0.26 -0.33 -0.6 -1.1 2.1 -0.95 -1.1 5e+03 0.00043 10 0.98 ++
1 -0.51 0.26 -0.33 -0.6 -1.1 2.1 -0.95 -1.1 5e+03 9.4e-07 10 1 ++
1 -0.51 0.26 -0.33 -0.6 -1.1 2.1 -0.95 -1.1 5e+03 9.4e-07 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.61 0.4 -0.29 -0.5 -1 1.8 -1.2 -1.3 4.9e+03 0.00038 10 1 ++
0 -0.61 0.4 -0.29 -0.5 -1 1.8 -1.2 -1.3 4.9e+03 0.00038 10 1 ++
1 -0.61 0.4 -0.29 -0.5 -1 1.8 -1.2 -1.3 4.9e+03 7e-07 10 1 ++
1 -0.61 0.4 -0.29 -0.5 -1 1.8 -1.2 -1.3 4.9e+03 7e-07 10 1 ++
24%|██▍ | 24/100 [00:01<00:03, 20.99it/s]Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.36 0.037 -0.17 -0.53 -1.2 1.9 -1 -0.94 5.1e+03 0.0015 10 0.96 ++
0 -0.36 0.037 -0.17 -0.53 -1.2 1.9 -1 -0.94 5.1e+03 0.0015 10 0.96 ++
1 -0.36 0.037 -0.17 -0.53 -1.2 1.9 -1 -0.94 5.1e+03 8.6e-06 10 1 ++
1 -0.36 0.037 -0.17 -0.53 -1.2 1.9 -1 -0.94 5.1e+03 8.6e-06 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.29 0.21 -0.56 -0.57 -0.98 1.9 -0.91 -1.2 5e+03 0.0009 10 0.97 ++
0 -0.29 0.21 -0.56 -0.57 -0.98 1.9 -0.91 -1.2 5e+03 0.0009 10 0.97 ++
1 -0.29 0.21 -0.56 -0.57 -0.98 1.9 -0.91 -1.2 5e+03 3.6e-06 10 1 ++
1 -0.29 0.21 -0.56 -0.57 -0.98 1.9 -0.91 -1.2 5e+03 3.6e-06 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.72 0.58 -0.57 -0.53 -1 2 -1 -1.3 4.9e+03 0.00027 10 1 ++
0 -0.72 0.58 -0.57 -0.53 -1 2 -1 -1.3 4.9e+03 0.00027 10 1 ++
1 -0.72 0.58 -0.57 -0.53 -1 2 -1 -1.3 4.9e+03 3.6e-07 10 1 ++
1 -0.72 0.58 -0.57 -0.53 -1 2 -1 -1.3 4.9e+03 3.6e-07 10 1 ++
27%|██▋ | 27/100 [00:01<00:03, 21.08it/s]Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.31 0.16 -0.15 -0.31 -1.2 1.9 -1.1 -1.3 4.9e+03 0.00057 10 1 ++
0 -0.31 0.16 -0.15 -0.31 -1.2 1.9 -1.1 -1.3 4.9e+03 0.00057 10 1 ++
1 -0.31 0.16 -0.15 -0.31 -1.2 1.9 -1.1 -1.3 4.9e+03 3e-06 10 1 ++
1 -0.31 0.16 -0.15 -0.31 -1.2 1.9 -1.1 -1.3 4.9e+03 3e-06 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.56 0.35 -0.34 -0.66 -1 1.9 -1.2 -1.2 4.9e+03 0.00017 10 1 ++
0 -0.56 0.35 -0.34 -0.66 -1 1.9 -1.2 -1.2 4.9e+03 0.00017 10 1 ++
1 -0.56 0.35 -0.34 -0.66 -1 1.9 -1.2 -1.2 4.9e+03 1.8e-07 10 1 ++
1 -0.56 0.35 -0.34 -0.66 -1 1.9 -1.2 -1.2 4.9e+03 1.8e-07 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.57 0.37 -0.76 -0.56 -1.1 1.8 -0.97 -1.1 5e+03 0.00031 10 0.99 ++
0 -0.57 0.37 -0.76 -0.56 -1.1 1.8 -0.97 -1.1 5e+03 0.00031 10 0.99 ++
1 -0.57 0.37 -0.76 -0.56 -1.1 1.8 -0.97 -1.1 5e+03 1.5e-06 10 1 ++
1 -0.57 0.37 -0.76 -0.56 -1.1 1.8 -0.97 -1.1 5e+03 1.5e-06 10 1 ++
30%|███ | 30/100 [00:01<00:03, 21.04it/s]Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.44 0.22 -0.72 -0.47 -1.1 1.8 -1.1 -1.2 5e+03 0.00028 10 1 ++
0 -0.44 0.22 -0.72 -0.47 -1.1 1.8 -1.1 -1.2 5e+03 0.00028 10 1 ++
1 -0.44 0.22 -0.72 -0.47 -1.1 1.8 -1.1 -1.2 5e+03 2.6e-06 10 1 ++
1 -0.44 0.22 -0.72 -0.47 -1.1 1.8 -1.1 -1.2 5e+03 2.6e-06 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.61 0.41 -0.41 -0.53 -1.1 1.9 -1.1 -1.2 5e+03 4.7e-05 1 1
0 -0.61 0.41 -0.41 -0.53 -1.1 1.9 -1.1 -1.2 5e+03 4.7e-05 1 1
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.69 0.53 -0.39 -0.67 -1 2 -1.1 -1.1 5e+03 0.00045 10 0.99 ++
0 -0.69 0.53 -0.39 -0.67 -1 2 -1.1 -1.1 5e+03 0.00045 10 0.99 ++
1 -0.69 0.53 -0.39 -0.67 -1 2 -1.1 -1.1 5e+03 5.1e-07 10 1 ++
1 -0.69 0.53 -0.39 -0.67 -1 2 -1.1 -1.1 5e+03 5.1e-07 10 1 ++
33%|███▎ | 33/100 [00:01<00:03, 21.76it/s]Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.66 0.57 -0.44 -0.49 -1.1 1.9 -0.97 -1.2 5e+03 0.00037 10 0.98 ++
0 -0.66 0.57 -0.44 -0.49 -1.1 1.9 -0.97 -1.2 5e+03 0.00037 10 0.98 ++
1 -0.66 0.57 -0.44 -0.49 -1.1 1.9 -0.97 -1.2 5e+03 5.9e-07 10 1 ++
1 -0.66 0.57 -0.44 -0.49 -1.1 1.9 -0.97 -1.2 5e+03 5.9e-07 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.69 0.41 -0.39 -0.53 -1.2 1.9 -1.1 -1 5e+03 0.00046 10 0.98 ++
0 -0.69 0.41 -0.39 -0.53 -1.2 1.9 -1.1 -1 5e+03 0.00046 10 0.98 ++
1 -0.69 0.41 -0.39 -0.53 -1.2 1.9 -1.1 -1 5e+03 5.5e-07 10 1 ++
1 -0.69 0.41 -0.39 -0.53 -1.2 1.9 -1.1 -1 5e+03 5.5e-07 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.78 0.54 -0.72 -0.57 -1.1 2 -1 -1.1 5e+03 0.00037 10 1 ++
0 -0.78 0.54 -0.72 -0.57 -1.1 2 -1 -1.1 5e+03 0.00037 10 1 ++
1 -0.78 0.54 -0.72 -0.57 -1.1 2 -1 -1.1 5e+03 5.5e-06 10 1 ++
1 -0.78 0.54 -0.72 -0.57 -1.1 2 -1 -1.1 5e+03 5.5e-06 10 1 ++
36%|███▌ | 36/100 [00:01<00:02, 21.44it/s]Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.72 0.54 -0.39 -0.44 -1.1 1.9 -1.1 -1.2 4.9e+03 0.00016 10 1 ++
0 -0.72 0.54 -0.39 -0.44 -1.1 1.9 -1.1 -1.2 4.9e+03 0.00016 10 1 ++
1 -0.72 0.54 -0.39 -0.44 -1.1 1.9 -1.1 -1.2 4.9e+03 1.5e-07 10 1 ++
1 -0.72 0.54 -0.39 -0.44 -1.1 1.9 -1.1 -1.2 4.9e+03 1.5e-07 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.59 0.34 -0.13 -0.69 -1.1 2 -1.1 -1.2 4.8e+03 0.00055 10 1 ++
0 -0.59 0.34 -0.13 -0.69 -1.1 2 -1.1 -1.2 4.8e+03 0.00055 10 1 ++
1 -0.59 0.34 -0.13 -0.69 -1.1 2 -1.1 -1.2 4.8e+03 1.5e-06 10 1 ++
1 -0.59 0.34 -0.13 -0.69 -1.1 2 -1.1 -1.2 4.8e+03 1.5e-06 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.72 0.48 -0.55 -0.61 -1.1 1.7 -0.97 -1 5e+03 0.00038 10 0.98 ++
0 -0.72 0.48 -0.55 -0.61 -1.1 1.7 -0.97 -1 5e+03 0.00038 10 0.98 ++
1 -0.72 0.48 -0.55 -0.61 -1.1 1.7 -0.97 -1 5e+03 9e-07 10 1 ++
1 -0.72 0.48 -0.55 -0.61 -1.1 1.7 -0.97 -1 5e+03 9e-07 10 1 ++
39%|███▉ | 39/100 [00:01<00:02, 21.29it/s]Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.59 0.37 -0.34 -0.48 -1.2 1.8 -1.1 -1.1 5e+03 0.00033 10 0.99 ++
0 -0.59 0.37 -0.34 -0.48 -1.2 1.8 -1.1 -1.1 5e+03 0.00033 10 0.99 ++
1 -0.59 0.37 -0.34 -0.48 -1.2 1.8 -1.1 -1.1 5e+03 2.8e-07 10 1 ++
1 -0.59 0.37 -0.34 -0.48 -1.2 1.8 -1.1 -1.1 5e+03 2.8e-07 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.58 0.44 -0.67 -0.41 -1.1 1.7 -0.92 -1.3 4.9e+03 0.00045 10 1 ++
0 -0.58 0.44 -0.67 -0.41 -1.1 1.7 -0.92 -1.3 4.9e+03 0.00045 10 1 ++
1 -0.58 0.44 -0.67 -0.41 -1.1 1.7 -0.92 -1.3 4.9e+03 9.7e-07 10 1 ++
1 -0.58 0.44 -0.67 -0.41 -1.1 1.7 -0.92 -1.3 4.9e+03 9.7e-07 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.57 0.13 -0.038 -0.86 -0.95 1.9 -1.1 -0.88 5e+03 0.0014 10 0.97 ++
0 -0.57 0.13 -0.038 -0.86 -0.95 1.9 -1.1 -0.88 5e+03 0.0014 10 0.97 ++
1 -0.57 0.13 -0.038 -0.86 -0.95 1.9 -1.1 -0.88 5e+03 7.2e-06 10 1 ++
1 -0.57 0.13 -0.038 -0.86 -0.95 1.9 -1.1 -0.88 5e+03 7.2e-06 10 1 ++
42%|████▏ | 42/100 [00:01<00:02, 21.21it/s]Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.6 0.45 -0.57 -0.58 -1.1 2 -1 -1.2 4.9e+03 0.00022 10 1 ++
0 -0.6 0.45 -0.57 -0.58 -1.1 2 -1 -1.2 4.9e+03 0.00022 10 1 ++
1 -0.6 0.45 -0.57 -0.58 -1.1 2 -1 -1.2 4.9e+03 2.3e-07 10 1 ++
1 -0.6 0.45 -0.57 -0.58 -1.1 2 -1 -1.2 4.9e+03 2.3e-07 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.65 0.41 -0.44 -0.61 -1.1 1.9 -1.2 -1.2 4.9e+03 0.00023 10 1 ++
0 -0.65 0.41 -0.44 -0.61 -1.1 1.9 -1.2 -1.2 4.9e+03 0.00023 10 1 ++
1 -0.65 0.41 -0.44 -0.61 -1.1 1.9 -1.2 -1.2 4.9e+03 2.8e-07 10 1 ++
1 -0.65 0.41 -0.44 -0.61 -1.1 1.9 -1.2 -1.2 4.9e+03 2.8e-07 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.57 0.38 -0.52 -0.45 -1.3 2 -1 -1.1 5e+03 0.00023 10 1 ++
0 -0.57 0.38 -0.52 -0.45 -1.3 2 -1 -1.1 5e+03 0.00023 10 1 ++
1 -0.57 0.38 -0.52 -0.45 -1.3 2 -1 -1.1 5e+03 2.2e-07 10 1 ++
1 -0.57 0.38 -0.52 -0.45 -1.3 2 -1 -1.1 5e+03 2.2e-07 10 1 ++
45%|████▌ | 45/100 [00:02<00:02, 21.19it/s]Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.82 0.51 -0.28 -0.76 -1 2 -1.1 -1.1 4.9e+03 0.00028 10 1 ++
0 -0.82 0.51 -0.28 -0.76 -1 2 -1.1 -1.1 4.9e+03 0.00028 10 1 ++
1 -0.82 0.51 -0.28 -0.76 -1 2 -1.1 -1.1 4.9e+03 3.2e-07 10 1 ++
1 -0.82 0.51 -0.28 -0.76 -1 2 -1.1 -1.1 4.9e+03 3.2e-07 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.6 0.43 -0.41 -0.43 -1.1 1.9 -1.1 -1.3 4.9e+03 0.00027 10 1 ++
0 -0.6 0.43 -0.41 -0.43 -1.1 1.9 -1.1 -1.3 4.9e+03 0.00027 10 1 ++
1 -0.6 0.43 -0.41 -0.43 -1.1 1.9 -1.1 -1.3 4.9e+03 1.7e-07 10 1 ++
1 -0.6 0.43 -0.41 -0.43 -1.1 1.9 -1.1 -1.3 4.9e+03 1.7e-07 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.58 0.31 -0.19 -0.77 -0.83 1.8 -0.97 -0.97 5.1e+03 0.0015 10 0.95 ++
0 -0.58 0.31 -0.19 -0.77 -0.83 1.8 -0.97 -0.97 5.1e+03 0.0015 10 0.95 ++
1 -0.58 0.31 -0.19 -0.77 -0.83 1.8 -0.97 -0.97 5.1e+03 8.1e-06 10 1 ++
1 -0.58 0.31 -0.19 -0.77 -0.83 1.8 -0.97 -0.97 5.1e+03 8.1e-06 10 1 ++
48%|████▊ | 48/100 [00:02<00:02, 21.08it/s]Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.59 0.36 -0.59 -0.61 -1 2 -1.1 -1.2 4.9e+03 0.00024 10 1 ++
0 -0.59 0.36 -0.59 -0.61 -1 2 -1.1 -1.2 4.9e+03 0.00024 10 1 ++
1 -0.59 0.36 -0.59 -0.61 -1 2 -1.1 -1.2 4.9e+03 1.6e-06 10 1 ++
1 -0.59 0.36 -0.59 -0.61 -1 2 -1.1 -1.2 4.9e+03 1.6e-06 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.61 0.41 -0.41 -0.53 -1.1 1.9 -1.1 -1.2 4.9e+03 8.7e-05 1 1
0 -0.61 0.41 -0.41 -0.53 -1.1 1.9 -1.1 -1.2 4.9e+03 8.7e-05 1 1
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.56 0.36 -0.29 -0.41 -1.1 1.7 -1.2 -1.2 5e+03 0.00024 10 1 ++
0 -0.56 0.36 -0.29 -0.41 -1.1 1.7 -1.2 -1.2 5e+03 0.00024 10 1 ++
1 -0.56 0.36 -0.29 -0.41 -1.1 1.7 -1.2 -1.2 5e+03 2.8e-07 10 1 ++
1 -0.56 0.36 -0.29 -0.41 -1.1 1.7 -1.2 -1.2 5e+03 2.8e-07 10 1 ++
51%|█████ | 51/100 [00:02<00:02, 21.53it/s]Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.68 0.5 -0.36 -0.64 -0.98 1.9 -1.2 -1.3 4.9e+03 0.00043 10 1 ++
0 -0.68 0.5 -0.36 -0.64 -0.98 1.9 -1.2 -1.3 4.9e+03 0.00043 10 1 ++
1 -0.68 0.5 -0.36 -0.64 -0.98 1.9 -1.2 -1.3 4.9e+03 8.4e-07 10 1 ++
1 -0.68 0.5 -0.36 -0.64 -0.98 1.9 -1.2 -1.3 4.9e+03 8.4e-07 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.57 0.36 -0.32 -0.51 -1.1 1.9 -1.2 -1.3 4.9e+03 0.00046 10 1 ++
0 -0.57 0.36 -0.32 -0.51 -1.1 1.9 -1.2 -1.3 4.9e+03 0.00046 10 1 ++
1 -0.57 0.36 -0.32 -0.51 -1.1 1.9 -1.2 -1.3 4.9e+03 1.1e-06 10 1 ++
1 -0.57 0.36 -0.32 -0.51 -1.1 1.9 -1.2 -1.3 4.9e+03 1.1e-06 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.66 0.45 -0.38 -0.4 -1.2 1.8 -1 -1.2 5e+03 0.00023 10 1 ++
0 -0.66 0.45 -0.38 -0.4 -1.2 1.8 -1 -1.2 5e+03 0.00023 10 1 ++
1 -0.66 0.45 -0.38 -0.4 -1.2 1.8 -1 -1.2 5e+03 1.4e-07 10 1 ++
1 -0.66 0.45 -0.38 -0.4 -1.2 1.8 -1 -1.2 5e+03 1.4e-07 10 1 ++
54%|█████▍ | 54/100 [00:02<00:02, 21.21it/s]Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.63 0.37 -0.025 -0.6 -1.1 2 -1.3 -1.1 4.9e+03 0.00041 10 1 ++
0 -0.63 0.37 -0.025 -0.6 -1.1 2 -1.3 -1.1 4.9e+03 0.00041 10 1 ++
1 -0.63 0.37 -0.025 -0.6 -1.1 2 -1.3 -1.1 4.9e+03 1.2e-06 10 1 ++
1 -0.63 0.37 -0.025 -0.6 -1.1 2 -1.3 -1.1 4.9e+03 1.2e-06 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.68 0.54 -0.76 -0.41 -1.2 1.7 -1.1 -1.3 4.9e+03 0.00025 10 1 ++
0 -0.68 0.54 -0.76 -0.41 -1.2 1.7 -1.1 -1.3 4.9e+03 0.00025 10 1 ++
1 -0.68 0.54 -0.76 -0.41 -1.2 1.7 -1.1 -1.3 4.9e+03 1.4e-06 10 1 ++
1 -0.68 0.54 -0.76 -0.41 -1.2 1.7 -1.1 -1.3 4.9e+03 1.4e-06 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.61 0.41 -0.41 -0.53 -1.1 1.9 -1.1 -1.2 4.9e+03 0.0001 1 0.99
0 -0.61 0.41 -0.41 -0.53 -1.1 1.9 -1.1 -1.2 4.9e+03 0.0001 1 0.99
57%|█████▋ | 57/100 [00:02<00:01, 21.70it/s]Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.75 0.45 -0.35 -0.74 -1.1 2 -1.1 -0.96 5e+03 0.00094 10 0.97 ++
0 -0.75 0.45 -0.35 -0.74 -1.1 2 -1.1 -0.96 5e+03 0.00094 10 0.97 ++
1 -0.75 0.45 -0.35 -0.74 -1.1 2 -1.1 -0.96 5e+03 2.4e-06 10 1 ++
1 -0.75 0.45 -0.35 -0.74 -1.1 2 -1.1 -0.96 5e+03 2.4e-06 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.48 0.37 -0.42 -0.49 -1 1.9 -0.96 -1.2 5e+03 0.00023 10 0.99 ++
0 -0.48 0.37 -0.42 -0.49 -1 1.9 -0.96 -1.2 5e+03 0.00023 10 0.99 ++
1 -0.48 0.37 -0.42 -0.49 -1 1.9 -0.96 -1.2 5e+03 3.5e-07 10 1 ++
1 -0.48 0.37 -0.42 -0.49 -1 1.9 -0.96 -1.2 5e+03 3.5e-07 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.5 0.32 -0.31 -0.44 -1.1 1.9 -1.1 -1.3 4.9e+03 0.00033 10 1 ++
0 -0.5 0.32 -0.31 -0.44 -1.1 1.9 -1.1 -1.3 4.9e+03 0.00033 10 1 ++
1 -0.5 0.32 -0.31 -0.44 -1.1 1.9 -1.1 -1.3 4.9e+03 2.9e-07 10 1 ++
1 -0.5 0.32 -0.31 -0.44 -1.1 1.9 -1.1 -1.3 4.9e+03 2.9e-07 10 1 ++
60%|██████ | 60/100 [00:02<00:01, 21.50it/s]Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.75 0.49 -0.28 -0.65 -1.1 1.9 -1.1 -1.1 4.9e+03 0.00017 10 1 ++
0 -0.75 0.49 -0.28 -0.65 -1.1 1.9 -1.1 -1.1 4.9e+03 0.00017 10 1 ++
1 -0.75 0.49 -0.28 -0.65 -1.1 1.9 -1.1 -1.1 4.9e+03 7.9e-08 10 1 ++
1 -0.75 0.49 -0.28 -0.65 -1.1 1.9 -1.1 -1.1 4.9e+03 7.9e-08 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.46 0.28 -0.28 -0.42 -1.1 2 -1.1 -1.3 4.9e+03 0.00049 10 1 ++
0 -0.46 0.28 -0.28 -0.42 -1.1 2 -1.1 -1.3 4.9e+03 0.00049 10 1 ++
1 -0.46 0.28 -0.28 -0.42 -1.1 2 -1.1 -1.3 4.9e+03 8e-07 10 1 ++
1 -0.46 0.28 -0.28 -0.42 -1.1 2 -1.1 -1.3 4.9e+03 8e-07 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.61 0.41 -0.41 -0.53 -1.1 1.9 -1.1 -1.2 5e+03 0.0001 1 1
0 -0.61 0.41 -0.41 -0.53 -1.1 1.9 -1.1 -1.2 5e+03 0.0001 1 1
63%|██████▎ | 63/100 [00:02<00:01, 21.94it/s]Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.69 0.45 -0.33 -0.58 -1.2 1.9 -1.2 -1.1 5e+03 0.00029 10 1 ++
0 -0.69 0.45 -0.33 -0.58 -1.2 1.9 -1.2 -1.1 5e+03 0.00029 10 1 ++
1 -0.69 0.45 -0.33 -0.58 -1.2 1.9 -1.2 -1.1 5e+03 2.6e-07 10 1 ++
1 -0.69 0.45 -0.33 -0.58 -1.2 1.9 -1.2 -1.1 5e+03 2.6e-07 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.61 0.41 -0.41 -0.53 -1.1 1.9 -1.1 -1.2 4.9e+03 0.00012 1 1
0 -0.61 0.41 -0.41 -0.53 -1.1 1.9 -1.1 -1.2 4.9e+03 0.00012 1 1
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.66 0.46 -0.26 -0.64 -1.1 1.9 -1.2 -1.2 4.9e+03 0.00019 10 1 ++
0 -0.66 0.46 -0.26 -0.64 -1.1 1.9 -1.2 -1.2 4.9e+03 0.00019 10 1 ++
1 -0.66 0.46 -0.26 -0.64 -1.1 1.9 -1.2 -1.2 4.9e+03 2e-07 10 1 ++
1 -0.66 0.46 -0.26 -0.64 -1.1 1.9 -1.2 -1.2 4.9e+03 2e-07 10 1 ++
66%|██████▌ | 66/100 [00:03<00:01, 22.18it/s]Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.5 0.26 -0.21 -0.56 -1 1.8 -1.2 -1.2 5e+03 0.00034 10 1 ++
0 -0.5 0.26 -0.21 -0.56 -1 1.8 -1.2 -1.2 5e+03 0.00034 10 1 ++
1 -0.5 0.26 -0.21 -0.56 -1 1.8 -1.2 -1.2 5e+03 5.2e-07 10 1 ++
1 -0.5 0.26 -0.21 -0.56 -1 1.8 -1.2 -1.2 5e+03 5.2e-07 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.65 0.44 -0.63 -0.52 -1.3 2.1 -1.2 -1.2 4.8e+03 0.00073 10 1 ++
0 -0.65 0.44 -0.63 -0.52 -1.3 2.1 -1.2 -1.2 4.8e+03 0.00073 10 1 ++
1 -0.65 0.44 -0.63 -0.52 -1.3 2.1 -1.2 -1.2 4.8e+03 6.6e-06 10 1 ++
1 -0.65 0.44 -0.63 -0.52 -1.3 2.1 -1.2 -1.2 4.8e+03 6.6e-06 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.57 0.32 -0.33 -0.62 -1.1 1.8 -1.1 -1.1 5e+03 0.00034 10 0.98 ++
0 -0.57 0.32 -0.33 -0.62 -1.1 1.8 -1.1 -1.1 5e+03 0.00034 10 0.98 ++
1 -0.57 0.32 -0.33 -0.62 -1.1 1.8 -1.1 -1.1 5e+03 3.9e-07 10 1 ++
1 -0.57 0.32 -0.33 -0.62 -1.1 1.8 -1.1 -1.1 5e+03 3.9e-07 10 1 ++
69%|██████▉ | 69/100 [00:03<00:01, 21.81it/s]Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.46 0.29 -0.098 -0.47 -1.1 1.9 -1.2 -1.2 5e+03 0.00058 10 1 ++
0 -0.46 0.29 -0.098 -0.47 -1.1 1.9 -1.2 -1.2 5e+03 0.00058 10 1 ++
1 -0.46 0.29 -0.098 -0.47 -1.1 1.9 -1.2 -1.2 5e+03 1.9e-06 10 1 ++
1 -0.46 0.29 -0.098 -0.47 -1.1 1.9 -1.2 -1.2 5e+03 1.9e-06 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.61 0.47 -0.34 -0.38 -1.2 1.8 -1.1 -1.3 4.9e+03 0.00032 10 1 ++
0 -0.61 0.47 -0.34 -0.38 -1.2 1.8 -1.1 -1.3 4.9e+03 0.00032 10 1 ++
1 -0.61 0.47 -0.34 -0.38 -1.2 1.8 -1.1 -1.3 4.9e+03 1.7e-07 10 1 ++
1 -0.61 0.47 -0.34 -0.38 -1.2 1.8 -1.1 -1.3 4.9e+03 1.7e-07 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.52 0.3 -0.48 -0.53 -1.2 1.9 -1 -1.2 4.9e+03 0.00043 10 1 ++
0 -0.52 0.3 -0.48 -0.53 -1.2 1.9 -1 -1.2 4.9e+03 0.00043 10 1 ++
1 -0.52 0.3 -0.48 -0.53 -1.2 1.9 -1 -1.2 4.9e+03 1.1e-06 10 1 ++
1 -0.52 0.3 -0.48 -0.53 -1.2 1.9 -1 -1.2 4.9e+03 1.1e-06 10 1 ++
72%|███████▏ | 72/100 [00:03<00:01, 21.28it/s]Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.59 0.46 -0.31 -0.39 -1.1 1.8 -1.1 -1.3 4.9e+03 0.00049 10 1 ++
0 -0.59 0.46 -0.31 -0.39 -1.1 1.8 -1.1 -1.3 4.9e+03 0.00049 10 1 ++
1 -0.59 0.46 -0.31 -0.39 -1.1 1.8 -1.1 -1.3 4.9e+03 5.4e-07 10 1 ++
1 -0.59 0.46 -0.31 -0.39 -1.1 1.8 -1.1 -1.3 4.9e+03 5.4e-07 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.56 0.21 -0.59 -0.61 -1.2 1.9 -1 -1 4.9e+03 0.00031 10 0.99 ++
0 -0.56 0.21 -0.59 -0.61 -1.2 1.9 -1 -1 4.9e+03 0.00031 10 0.99 ++
1 -0.56 0.21 -0.59 -0.61 -1.2 1.9 -1 -1 4.9e+03 1.4e-06 10 1 ++
1 -0.56 0.21 -0.59 -0.61 -1.2 1.9 -1 -1 4.9e+03 1.4e-06 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.62 0.5 -1 -0.41 -1.1 1.8 -0.95 -1.3 5e+03 0.00055 10 1 ++
0 -0.62 0.5 -1 -0.41 -1.1 1.8 -0.95 -1.3 5e+03 0.00055 10 1 ++
1 -0.62 0.5 -1 -0.41 -1.1 1.8 -0.95 -1.3 5e+03 2.2e-05 10 1 ++
1 -0.62 0.5 -1 -0.41 -1.1 1.8 -0.95 -1.3 5e+03 2.2e-05 10 1 ++
75%|███████▌ | 75/100 [00:03<00:01, 21.15it/s]Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.61 0.41 -0.41 -0.53 -1.1 1.9 -1.1 -1.2 4.9e+03 0.00011 1 1
0 -0.61 0.41 -0.41 -0.53 -1.1 1.9 -1.1 -1.2 4.9e+03 0.00011 1 1
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.57 0.3 -0.13 -0.65 -1.1 2 -1.2 -1.1 4.9e+03 0.00028 10 0.99 ++
0 -0.57 0.3 -0.13 -0.65 -1.1 2 -1.2 -1.1 4.9e+03 0.00028 10 0.99 ++
1 -0.57 0.3 -0.13 -0.65 -1.1 2 -1.2 -1.1 4.9e+03 4.7e-07 10 1 ++
1 -0.57 0.3 -0.13 -0.65 -1.1 2 -1.2 -1.1 4.9e+03 4.7e-07 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.61 0.41 -0.41 -0.53 -1.1 1.9 -1.1 -1.2 4.9e+03 0.00011 1 1
0 -0.61 0.41 -0.41 -0.53 -1.1 1.9 -1.1 -1.2 4.9e+03 0.00011 1 1
78%|███████▊ | 78/100 [00:03<00:00, 22.50it/s]Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.66 0.53 -0.62 -0.5 -1.1 1.8 -1 -1.2 5e+03 0.00013 10 1 ++
0 -0.66 0.53 -0.62 -0.5 -1.1 1.8 -1 -1.2 5e+03 0.00013 10 1 ++
1 -0.66 0.53 -0.62 -0.5 -1.1 1.8 -1 -1.2 5e+03 1.3e-07 10 1 ++
1 -0.66 0.53 -0.62 -0.5 -1.1 1.8 -1 -1.2 5e+03 1.3e-07 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.67 0.51 -0.49 -0.44 -1.1 2 -1.1 -1.3 4.9e+03 0.00038 10 1 ++
0 -0.67 0.51 -0.49 -0.44 -1.1 2 -1.1 -1.3 4.9e+03 0.00038 10 1 ++
1 -0.67 0.51 -0.49 -0.44 -1.1 2 -1.1 -1.3 4.9e+03 5.2e-07 10 1 ++
1 -0.67 0.51 -0.49 -0.44 -1.1 2 -1.1 -1.3 4.9e+03 5.2e-07 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.75 0.62 -0.39 -0.55 -1 1.9 -0.95 -1.1 5e+03 0.00043 10 0.98 ++
0 -0.75 0.62 -0.39 -0.55 -1 1.9 -0.95 -1.1 5e+03 0.00043 10 0.98 ++
1 -0.75 0.62 -0.39 -0.55 -1 1.9 -0.95 -1.1 5e+03 9.5e-07 10 1 ++
1 -0.75 0.62 -0.39 -0.55 -1 1.9 -0.95 -1.1 5e+03 9.5e-07 10 1 ++
81%|████████ | 81/100 [00:03<00:00, 22.09it/s]Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.45 0.23 -0.33 -0.55 -1 1.8 -1.1 -1.2 5e+03 0.00018 10 0.97 ++
0 -0.45 0.23 -0.33 -0.55 -1 1.8 -1.1 -1.2 5e+03 0.00018 10 0.97 ++
1 -0.45 0.23 -0.33 -0.55 -1 1.8 -1.1 -1.2 5e+03 4e-07 10 1 ++
1 -0.45 0.23 -0.33 -0.55 -1 1.8 -1.1 -1.2 5e+03 4e-07 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.62 0.48 -0.76 -0.42 -1.1 1.9 -0.98 -1.2 5e+03 0.00022 10 1 ++
0 -0.62 0.48 -0.76 -0.42 -1.1 1.9 -0.98 -1.2 5e+03 0.00022 10 1 ++
1 -0.62 0.48 -0.76 -0.42 -1.1 1.9 -0.98 -1.2 5e+03 1.6e-06 10 1 ++
1 -0.62 0.48 -0.76 -0.42 -1.1 1.9 -0.98 -1.2 5e+03 1.6e-06 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.63 0.29 -0.24 -0.53 -1.2 2 -1.2 -1 5e+03 0.0006 10 0.99 ++
0 -0.63 0.29 -0.24 -0.53 -1.2 2 -1.2 -1 5e+03 0.0006 10 0.99 ++
1 -0.63 0.29 -0.24 -0.53 -1.2 2 -1.2 -1 5e+03 1e-06 10 1 ++
1 -0.63 0.29 -0.24 -0.53 -1.2 2 -1.2 -1 5e+03 1e-06 10 1 ++
84%|████████▍ | 84/100 [00:03<00:00, 21.88it/s]Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.6 0.26 -0.019 -0.65 -1.1 2 -1.2 -1.1 4.9e+03 0.00042 10 1 ++
0 -0.6 0.26 -0.019 -0.65 -1.1 2 -1.2 -1.1 4.9e+03 0.00042 10 1 ++
1 -0.6 0.26 -0.019 -0.65 -1.1 2 -1.2 -1.1 4.9e+03 1.2e-06 10 1 ++
1 -0.6 0.26 -0.019 -0.65 -1.1 2 -1.2 -1.1 4.9e+03 1.2e-06 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.57 0.31 -0.51 -0.63 -1.1 1.8 -0.95 -1 5e+03 0.00058 10 0.96 ++
0 -0.57 0.31 -0.51 -0.63 -1.1 1.8 -0.95 -1 5e+03 0.00058 10 0.96 ++
1 -0.57 0.31 -0.51 -0.63 -1.1 1.8 -0.95 -1 5e+03 2e-06 10 1 ++
1 -0.57 0.31 -0.51 -0.63 -1.1 1.8 -0.95 -1 5e+03 2e-06 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.52 0.35 -0.56 -0.6 -0.97 2 -1.1 -1.2 4.9e+03 0.00024 10 1 ++
0 -0.52 0.35 -0.56 -0.6 -0.97 2 -1.1 -1.2 4.9e+03 0.00024 10 1 ++
1 -0.52 0.35 -0.56 -0.6 -0.97 2 -1.1 -1.2 4.9e+03 1.1e-07 10 1 ++
1 -0.52 0.35 -0.56 -0.6 -0.97 2 -1.1 -1.2 4.9e+03 1.1e-07 10 1 ++
87%|████████▋ | 87/100 [00:04<00:00, 21.79it/s]Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.56 0.46 -0.15 -0.33 -1.2 1.9 -1.2 -1.4 4.9e+03 0.001 10 1 ++
0 -0.56 0.46 -0.15 -0.33 -1.2 1.9 -1.2 -1.4 4.9e+03 0.001 10 1 ++
1 -0.56 0.46 -0.15 -0.33 -1.2 1.9 -1.2 -1.4 4.9e+03 3.6e-06 10 1 ++
1 -0.56 0.46 -0.15 -0.33 -1.2 1.9 -1.2 -1.4 4.9e+03 3.6e-06 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.62 0.6 -0.56 -0.42 -1.1 1.8 -1 -1.4 4.8e+03 0.0016 10 1 ++
0 -0.62 0.6 -0.56 -0.42 -1.1 1.8 -1 -1.4 4.8e+03 0.0016 10 1 ++
1 -0.62 0.6 -0.56 -0.42 -1.1 1.8 -1 -1.4 4.8e+03 6.2e-06 10 1 ++
1 -0.62 0.6 -0.56 -0.42 -1.1 1.8 -1 -1.4 4.8e+03 6.2e-06 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.53 0.38 -0.4 -0.37 -1.1 1.9 -1.2 -1.3 4.9e+03 0.00033 10 1 ++
0 -0.53 0.38 -0.4 -0.37 -1.1 1.9 -1.2 -1.3 4.9e+03 0.00033 10 1 ++
1 -0.53 0.38 -0.4 -0.37 -1.1 1.9 -1.2 -1.3 4.9e+03 4.7e-07 10 1 ++
1 -0.53 0.38 -0.4 -0.37 -1.1 1.9 -1.2 -1.3 4.9e+03 4.7e-07 10 1 ++
90%|█████████ | 90/100 [00:04<00:00, 21.60it/s]Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.61 0.41 -0.41 -0.53 -1.1 1.9 -1.1 -1.2 5e+03 0.00011 1 1
0 -0.61 0.41 -0.41 -0.53 -1.1 1.9 -1.1 -1.2 5e+03 0.00011 1 1
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.54 0.39 -0.25 -0.49 -1.2 2 -1.1 -1.2 5e+03 0.00023 10 0.99 ++
0 -0.54 0.39 -0.25 -0.49 -1.2 2 -1.1 -1.2 5e+03 0.00023 10 0.99 ++
1 -0.54 0.39 -0.25 -0.49 -1.2 2 -1.1 -1.2 5e+03 5.8e-07 10 1 ++
1 -0.54 0.39 -0.25 -0.49 -1.2 2 -1.1 -1.2 5e+03 5.8e-07 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.48 0.37 -1 -0.44 -1.1 2 -1 -1.3 4.9e+03 0.00083 10 1.1 ++
0 -0.48 0.37 -1 -0.44 -1.1 2 -1 -1.3 4.9e+03 0.00083 10 1.1 ++
1 -0.48 0.37 -1 -0.44 -1.1 2 -1 -1.3 4.9e+03 5.1e-05 10 1 ++
1 -0.48 0.37 -1 -0.44 -1.1 2 -1 -1.3 4.9e+03 5.1e-05 10 1 ++
93%|█████████▎| 93/100 [00:04<00:00, 22.04it/s]Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.61 0.41 -0.41 -0.53 -1.1 1.9 -1.1 -1.2 4.9e+03 9.5e-05 1 1
0 -0.61 0.41 -0.41 -0.53 -1.1 1.9 -1.1 -1.2 4.9e+03 9.5e-05 1 1
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.61 0.41 -0.41 -0.53 -1.1 1.9 -1.1 -1.2 4.9e+03 9.4e-05 1 1
0 -0.61 0.41 -0.41 -0.53 -1.1 1.9 -1.1 -1.2 4.9e+03 9.4e-05 1 1
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.64 0.42 -0.073 -0.47 -1.1 2 -1 -1.1 5e+03 0.00031 10 0.99 ++
0 -0.64 0.42 -0.073 -0.47 -1.1 2 -1 -1.1 5e+03 0.00031 10 0.99 ++
1 -0.64 0.42 -0.073 -0.47 -1.1 2 -1 -1.1 5e+03 1.6e-06 10 1 ++
1 -0.64 0.42 -0.073 -0.47 -1.1 2 -1 -1.1 5e+03 1.6e-06 10 1 ++
96%|█████████▌| 96/100 [00:04<00:00, 23.13it/s]Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.71 0.4 -0.16 -0.56 -1.2 1.8 -1.1 -1 5e+03 0.00033 10 0.98 ++
0 -0.71 0.4 -0.16 -0.56 -1.2 1.8 -1.1 -1 5e+03 0.00033 10 0.98 ++
1 -0.71 0.4 -0.16 -0.56 -1.2 1.8 -1.1 -1 5e+03 8.6e-07 10 1 ++
1 -0.71 0.4 -0.16 -0.56 -1.2 1.8 -1.1 -1 5e+03 8.6e-07 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.49 0.32 -0.37 -0.41 -1.1 1.7 -1.1 -1.2 5e+03 0.00015 10 0.99 ++
0 -0.49 0.32 -0.37 -0.41 -1.1 1.7 -1.1 -1.2 5e+03 0.00015 10 0.99 ++
1 -0.49 0.32 -0.37 -0.41 -1.1 1.7 -1.1 -1.2 5e+03 1.1e-07 10 1 ++
1 -0.49 0.32 -0.37 -0.41 -1.1 1.7 -1.1 -1.2 5e+03 1.1e-07 10 1 ++
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.75 0.54 -0.62 -0.51 -1 1.9 -1.1 -1.3 4.9e+03 0.00071 10 1 ++
0 -0.75 0.54 -0.62 -0.51 -1 1.9 -1.1 -1.3 4.9e+03 0.00071 10 1 ++
1 -0.75 0.54 -0.62 -0.51 -1 1.9 -1.1 -1.3 4.9e+03 3.1e-06 10 1 ++
1 -0.75 0.54 -0.62 -0.51 -1 1.9 -1.1 -1.3 4.9e+03 3.1e-06 10 1 ++
99%|█████████▉| 99/100 [00:04<00:00, 22.36it/s]Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
** Optimization: Newton with trust region for simple bounds
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
Iter. ASC_CAR ASC_CAR_male ASC_CAR_with_ga ASC_TRAIN ASC_TRAIN_male ASC_TRAIN_with_ B_COST B_TIME Function Relgrad Radius Rho
0 -0.3 0.16 -0.23 -0.59 -1 1.8 -1.1 -1.2 5e+03 0.00072 10 0.96 ++
0 -0.3 0.16 -0.23 -0.59 -1 1.8 -1.1 -1.2 5e+03 0.00072 10 0.96 ++
1 -0.3 0.16 -0.23 -0.59 -1 1.8 -1.1 -1.2 5e+03 4.4e-06 10 1 ++
1 -0.3 0.16 -0.23 -0.59 -1 1.8 -1.1 -1.2 5e+03 4.4e-06 10 1 ++
100%|██████████| 100/100 [00:04<00:00, 21.54it/s]
Results saved in file b01logit_bis.html
Results saved in file b01logit_bis.html
Results saved in file b01logit_bis.pickle
Results saved in file b01logit_bis.pickle
Get the results in a pandas table.
print('Parameters')
print('----------')
pandas_results = results.get_estimated_parameters()
pandas_results
Parameters
----------
Get general statistics.
print('General statistics')
print('------------------')
stats = results.get_general_statistics()
for description, (value, formatting) in stats.items():
print(f'{description}: {value:{formatting}}')
General statistics
------------------
Number of estimated parameters: 8
Sample size: 6768
Excluded observations: 3960
Null log likelihood: -6964.663
Init log likelihood: -5533.155
Final log likelihood: -4943.895
Likelihood ratio test for the null model: 4041.535
Rho-square for the null model: 0.29
Rho-square-bar for the null model: 0.289
Likelihood ratio test for the init. model: 1178.519
Rho-square for the init. model: 0.106
Rho-square-bar for the init. model: 0.105
Akaike Information Criterion: 9903.791
Bayesian Information Criterion: 9958.351
Final gradient norm: 5.3376E-03
Bootstrapping time: 0:00:04.642499
Nbr of threads: 12
Messages from the optimization algorithm.
print('Optimization algorithm')
print('----------------------')
for description, message in results.data.optimizationMessages.items():
print(f'{description}:\t{message}')
Optimization algorithm
----------------------
Relative gradient: 6.556090431875208e-07
Cause of termination: Relative gradient = 6.6e-07 <= 0.00012
Number of function evaluations: 5
Number of gradient evaluations: 5
Number of hessian evaluations: 4
Algorithm: Newton with trust region for simple bound constraints
Number of iterations: 4
Proportion of Hessian calculation: 4/4 = 100.0%
Optimization time: 0:00:00.066021
Generate the file in Alogit format.
results.write_f12(robust_std_err=True)
print(f'Estimation results in ALogit format generated: {results.data.F12FileName}')
Results saved in file b01logit_bis~19.F12
Results saved in file b01logit_bis~19.F12
Estimation results in ALogit format generated: b01logit_bis~19.F12
Generate LaTeX code with the results.
results.write_latex()
print(f'Estimation results in LaTeX format generated: {results.data.latexFileName}')
Results saved in file b01logit_bis.tex
Results saved in file b01logit_bis.tex
Estimation results in LaTeX format generated: b01logit_bis.tex
Total running time of the script: (0 minutes 4.859 seconds)