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Calibration of a polynomial regression¶
from __future__ import annotations
import matplotlib.pyplot as plt
from gemseo import configure_logger
from gemseo.algos.design_space import DesignSpace
from gemseo.mlearning.core.calibration import MLAlgoCalibration
from gemseo.mlearning.quality_measures.mse_measure import MSEMeasure
from gemseo.problems.dataset.rosenbrock import create_rosenbrock_dataset
from matplotlib.tri import Triangulation
Load the dataset¶
dataset = create_rosenbrock_dataset(opt_naming=False, n_samples=25)
Define the measure¶
configure_logger()
test_dataset = create_rosenbrock_dataset(opt_naming=False)
measure_evaluation_method_name = "TEST"
measure_options = {"test_data": test_dataset}
Calibrate the degree of the polynomial regression¶
Define and execute the calibration¶
calibration_space = DesignSpace()
calibration_space.add_variable("degree", 1, "integer", 1, 10, 1)
calibration = MLAlgoCalibration(
"PolynomialRegressor",
dataset,
["degree"],
calibration_space,
MSEMeasure,
measure_evaluation_method_name=measure_evaluation_method_name,
measure_options=measure_options,
)
calibration.execute({"algo": "fullfact", "n_samples": 10})
x_opt = calibration.optimal_parameters
f_opt = calibration.optimal_criterion
degree = x_opt["degree"][0]
f"optimal degree = {degree}; optimal criterion = {f_opt}"
INFO - 13:53:01:
INFO - 13:53:01: *** Start DOEScenario execution ***
INFO - 13:53:01: DOEScenario
INFO - 13:53:01: Disciplines: MLAlgoAssessor
INFO - 13:53:01: MDO formulation: DisciplinaryOpt
INFO - 13:53:01: Optimization problem:
INFO - 13:53:01: minimize criterion(degree)
INFO - 13:53:01: with respect to degree
INFO - 13:53:01: over the design space:
INFO - 13:53:01: +--------+-------------+-------+-------------+---------+
INFO - 13:53:01: | name | lower_bound | value | upper_bound | type |
INFO - 13:53:01: +--------+-------------+-------+-------------+---------+
INFO - 13:53:01: | degree | 1 | 1 | 10 | integer |
INFO - 13:53:01: +--------+-------------+-------+-------------+---------+
INFO - 13:53:01: Solving optimization problem with algorithm fullfact:
INFO - 13:53:01: ... 0%| | 0/10 [00:00<?, ?it]
INFO - 13:53:01: ... 10%|█ | 1/10 [00:00<00:00, 28.44 it/sec, obj=5.89e+5]
INFO - 13:53:01: ... 20%|██ | 2/10 [00:00<00:00, 39.87 it/sec, obj=1.73e+5]
INFO - 13:53:01: ... 30%|███ | 3/10 [00:00<00:00, 46.04 it/sec, obj=3e+4]
INFO - 13:53:01: ... 40%|████ | 4/10 [00:00<00:00, 50.19 it/sec, obj=1.1e-24]
INFO - 13:53:01: ... 50%|█████ | 5/10 [00:00<00:00, 52.99 it/sec, obj=0.11]
INFO - 13:53:01: ... 60%|██████ | 6/10 [00:00<00:00, 54.83 it/sec, obj=1.18e+3]
INFO - 13:53:01: ... 70%|███████ | 7/10 [00:00<00:00, 56.39 it/sec, obj=6.9e+3]
INFO - 13:53:01: ... 80%|████████ | 8/10 [00:00<00:00, 57.60 it/sec, obj=1.36e+4]
INFO - 13:53:01: ... 90%|█████████ | 9/10 [00:00<00:00, 58.50 it/sec, obj=9.18e+4]
INFO - 13:53:01: ... 100%|██████████| 10/10 [00:00<00:00, 59.17 it/sec, obj=1.63e+5]
INFO - 13:53:01: Optimization result:
INFO - 13:53:01: Optimizer info:
INFO - 13:53:01: Status: None
INFO - 13:53:01: Message: None
INFO - 13:53:01: Number of calls to the objective function by the optimizer: 10
INFO - 13:53:01: Solution:
INFO - 13:53:01: Objective: 1.0957626812742524e-24
INFO - 13:53:01: Design space:
INFO - 13:53:01: +--------+-------------+-------+-------------+---------+
INFO - 13:53:01: | name | lower_bound | value | upper_bound | type |
INFO - 13:53:01: +--------+-------------+-------+-------------+---------+
INFO - 13:53:01: | degree | 1 | 4 | 10 | integer |
INFO - 13:53:01: +--------+-------------+-------+-------------+---------+
INFO - 13:53:01: *** End DOEScenario execution (time: 0:00:00.181544) ***
'optimal degree = 4; optimal criterion = 1.0957626812742524e-24'
Get the history¶
calibration.dataset
Visualize the results¶
degree = calibration.get_history("degree")
criterion = calibration.get_history("criterion")
learning = calibration.get_history("learning")
plt.plot(degree, criterion, "-o", label="test", color="red")
plt.plot(degree, learning, "-o", label="learning", color="blue")
plt.xlabel("polynomial degree")
plt.ylabel("quality")
plt.axvline(x_opt["degree"], color="red", ls="--")
plt.legend()
plt.show()
Calibrate the ridge penalty of the polynomial regression¶
Define and execute the calibration¶
calibration_space = DesignSpace()
calibration_space.add_variable("penalty_level", 1, "float", 0.0, 100.0, 0.0)
calibration = MLAlgoCalibration(
"PolynomialRegressor",
dataset,
["penalty_level"],
calibration_space,
MSEMeasure,
measure_evaluation_method_name=measure_evaluation_method_name,
measure_options=measure_options,
degree=10,
)
calibration.execute({"algo": "fullfact", "n_samples": 10})
x_opt = calibration.optimal_parameters
f_opt = calibration.optimal_criterion
x_opt["penalty_level"][0], f_opt
INFO - 13:53:01:
INFO - 13:53:01: *** Start DOEScenario execution ***
INFO - 13:53:01: DOEScenario
INFO - 13:53:01: Disciplines: MLAlgoAssessor
INFO - 13:53:01: MDO formulation: DisciplinaryOpt
INFO - 13:53:01: Optimization problem:
INFO - 13:53:01: minimize criterion(penalty_level)
INFO - 13:53:01: with respect to penalty_level
INFO - 13:53:01: over the design space:
INFO - 13:53:01: +---------------+-------------+-------+-------------+-------+
INFO - 13:53:01: | name | lower_bound | value | upper_bound | type |
INFO - 13:53:01: +---------------+-------------+-------+-------------+-------+
INFO - 13:53:01: | penalty_level | 0 | 0 | 100 | float |
INFO - 13:53:01: +---------------+-------------+-------+-------------+-------+
INFO - 13:53:01: Solving optimization problem with algorithm fullfact:
INFO - 13:53:01: ... 0%| | 0/10 [00:00<?, ?it]
INFO - 13:53:01: ... 10%|█ | 1/10 [00:00<00:00, 55.92 it/sec, obj=1.63e+5]
INFO - 13:53:01: ... 20%|██ | 2/10 [00:00<00:00, 58.81 it/sec, obj=3.25e+4]
INFO - 13:53:01: ... 30%|███ | 3/10 [00:00<00:00, 60.98 it/sec, obj=1.78e+4]
INFO - 13:53:01: ... 40%|████ | 4/10 [00:00<00:00, 62.24 it/sec, obj=1.72e+4]
INFO - 13:53:01: ... 50%|█████ | 5/10 [00:00<00:00, 63.25 it/sec, obj=2e+4]
INFO - 13:53:01: ... 60%|██████ | 6/10 [00:00<00:00, 63.52 it/sec, obj=2.35e+4]
INFO - 13:53:01: ... 70%|███████ | 7/10 [00:00<00:00, 64.11 it/sec, obj=2.7e+4]
INFO - 13:53:01: ... 80%|████████ | 8/10 [00:00<00:00, 64.50 it/sec, obj=3.03e+4]
INFO - 13:53:01: ... 90%|█████████ | 9/10 [00:00<00:00, 64.65 it/sec, obj=3.33e+4]
INFO - 13:53:01: ... 100%|██████████| 10/10 [00:00<00:00, 65.05 it/sec, obj=3.59e+4]
INFO - 13:53:01: Optimization result:
INFO - 13:53:01: Optimizer info:
INFO - 13:53:01: Status: None
INFO - 13:53:01: Message: None
INFO - 13:53:01: Number of calls to the objective function by the optimizer: 10
INFO - 13:53:01: Solution:
INFO - 13:53:01: Objective: 17189.52649297074
INFO - 13:53:01: Design space:
INFO - 13:53:01: +---------------+-------------+-------------------+-------------+-------+
INFO - 13:53:01: | name | lower_bound | value | upper_bound | type |
INFO - 13:53:01: +---------------+-------------+-------------------+-------------+-------+
INFO - 13:53:01: | penalty_level | 0 | 33.33333333333333 | 100 | float |
INFO - 13:53:01: +---------------+-------------+-------------------+-------------+-------+
INFO - 13:53:01: *** End DOEScenario execution (time: 0:00:00.166009) ***
(33.33333333333333, 17189.52649297074)
Get the history¶
calibration.dataset
Visualize the results¶
penalty_level = calibration.get_history("penalty_level")
criterion = calibration.get_history("criterion")
learning = calibration.get_history("learning")
plt.plot(penalty_level, criterion, "-o", label="test", color="red")
plt.plot(penalty_level, learning, "-o", label="learning", color="blue")
plt.axvline(x_opt["penalty_level"], color="red", ls="--")
plt.xlabel("ridge penalty")
plt.ylabel("quality")
plt.legend()
plt.show()
Calibrate the lasso penalty of the polynomial regression¶
Define and execute the calibration¶
calibration_space = DesignSpace()
calibration_space.add_variable("penalty_level", 1, "float", 0.0, 100.0, 0.0)
calibration = MLAlgoCalibration(
"PolynomialRegressor",
dataset,
["penalty_level"],
calibration_space,
MSEMeasure,
measure_evaluation_method_name=measure_evaluation_method_name,
measure_options=measure_options,
degree=10,
l2_penalty_ratio=0.0,
)
calibration.execute({"algo": "fullfact", "n_samples": 10})
x_opt = calibration.optimal_parameters
f_opt = calibration.optimal_criterion
x_opt["penalty_level"][0], f_opt
INFO - 13:53:02:
INFO - 13:53:02: *** Start DOEScenario execution ***
INFO - 13:53:02: DOEScenario
INFO - 13:53:02: Disciplines: MLAlgoAssessor
INFO - 13:53:02: MDO formulation: DisciplinaryOpt
INFO - 13:53:02: Optimization problem:
INFO - 13:53:02: minimize criterion(penalty_level)
INFO - 13:53:02: with respect to penalty_level
INFO - 13:53:02: over the design space:
INFO - 13:53:02: +---------------+-------------+-------+-------------+-------+
INFO - 13:53:02: | name | lower_bound | value | upper_bound | type |
INFO - 13:53:02: +---------------+-------------+-------+-------------+-------+
INFO - 13:53:02: | penalty_level | 0 | 0 | 100 | float |
INFO - 13:53:02: +---------------+-------------+-------+-------------+-------+
INFO - 13:53:02: Solving optimization problem with algorithm fullfact:
INFO - 13:53:02: ... 0%| | 0/10 [00:00<?, ?it]
INFO - 13:53:02: ... 10%|█ | 1/10 [00:00<00:00, 54.37 it/sec, obj=1.63e+5]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.301e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:02: ... 20%|██ | 2/10 [00:00<00:00, 50.89 it/sec, obj=1.58e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 4.631e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:02: ... 30%|███ | 3/10 [00:00<00:00, 51.42 it/sec, obj=3.15e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.284e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:02: ... 40%|████ | 4/10 [00:00<00:00, 51.92 it/sec, obj=4.74e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.984e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:02: ... 50%|█████ | 5/10 [00:00<00:00, 52.10 it/sec, obj=5.94e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.054e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:02: ... 60%|██████ | 6/10 [00:00<00:00, 51.88 it/sec, obj=6.27e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.152e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:02: ... 70%|███████ | 7/10 [00:00<00:00, 51.87 it/sec, obj=6.63e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.925e+03, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:02: ... 80%|████████ | 8/10 [00:00<00:00, 51.92 it/sec, obj=6.93e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.746e+03, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:02: ... 90%|█████████ | 9/10 [00:00<00:00, 52.11 it/sec, obj=7.25e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 6.372e+03, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:02: ... 100%|██████████| 10/10 [00:00<00:00, 52.39 it/sec, obj=7.57e+4]
INFO - 13:53:02: Optimization result:
INFO - 13:53:02: Optimizer info:
INFO - 13:53:02: Status: None
INFO - 13:53:02: Message: None
INFO - 13:53:02: Number of calls to the objective function by the optimizer: 10
INFO - 13:53:02: Solution:
INFO - 13:53:02: Objective: 15775.989581125898
INFO - 13:53:02: Design space:
INFO - 13:53:02: +---------------+-------------+-------------------+-------------+-------+
INFO - 13:53:02: | name | lower_bound | value | upper_bound | type |
INFO - 13:53:02: +---------------+-------------+-------------------+-------------+-------+
INFO - 13:53:02: | penalty_level | 0 | 11.11111111111111 | 100 | float |
INFO - 13:53:02: +---------------+-------------+-------------------+-------------+-------+
INFO - 13:53:02: *** End DOEScenario execution (time: 0:00:00.205355) ***
(11.11111111111111, 15775.989581125898)
Get the history¶
calibration.dataset
Visualize the results¶
penalty_level = calibration.get_history("penalty_level")
criterion = calibration.get_history("criterion")
learning = calibration.get_history("learning")
plt.plot(penalty_level, criterion, "-o", label="test", color="red")
plt.plot(penalty_level, learning, "-o", label="learning", color="blue")
plt.axvline(x_opt["penalty_level"], color="red", ls="--")
plt.xlabel("lasso penalty")
plt.ylabel("quality")
plt.legend()
plt.show()
Calibrate the elasticnet penalty of the polynomial regression¶
Define and execute the calibration¶
calibration_space = DesignSpace()
calibration_space.add_variable("penalty_level", 1, "float", 0.0, 40.0, 0.0)
calibration_space.add_variable("l2_penalty_ratio", 1, "float", 0.0, 1.0, 0.5)
calibration = MLAlgoCalibration(
"PolynomialRegressor",
dataset,
["penalty_level", "l2_penalty_ratio"],
calibration_space,
MSEMeasure,
measure_evaluation_method_name=measure_evaluation_method_name,
measure_options=measure_options,
degree=10,
)
calibration.execute({"algo": "fullfact", "n_samples": 100})
x_opt = calibration.optimal_parameters
f_opt = calibration.optimal_criterion
x_opt["penalty_level"][0], x_opt["l2_penalty_ratio"][0], f_opt
INFO - 13:53:02:
INFO - 13:53:02: *** Start DOEScenario execution ***
INFO - 13:53:02: DOEScenario
INFO - 13:53:02: Disciplines: MLAlgoAssessor
INFO - 13:53:02: MDO formulation: DisciplinaryOpt
INFO - 13:53:02: Optimization problem:
INFO - 13:53:02: minimize criterion(penalty_level, l2_penalty_ratio)
INFO - 13:53:02: with respect to l2_penalty_ratio, penalty_level
INFO - 13:53:02: over the design space:
INFO - 13:53:02: +------------------+-------------+-------+-------------+-------+
INFO - 13:53:02: | name | lower_bound | value | upper_bound | type |
INFO - 13:53:02: +------------------+-------------+-------+-------------+-------+
INFO - 13:53:02: | penalty_level | 0 | 0 | 40 | float |
INFO - 13:53:02: | l2_penalty_ratio | 0 | 0.5 | 1 | float |
INFO - 13:53:02: +------------------+-------------+-------+-------------+-------+
INFO - 13:53:02: Solving optimization problem with algorithm fullfact:
INFO - 13:53:02: ... 0%| | 0/100 [00:00<?, ?it]
INFO - 13:53:02: ... 1%| | 1/100 [00:00<00:01, 55.22 it/sec, obj=1.63e+5]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.904e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:02: ... 2%|▏ | 2/100 [00:00<00:01, 52.36 it/sec, obj=4.14e+3]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.786e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:02: ... 3%|▎ | 3/100 [00:00<00:01, 52.20 it/sec, obj=1.34e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.325e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:02: ... 4%|▍ | 4/100 [00:00<00:01, 51.98 it/sec, obj=1.79e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 4.034e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:02: ... 5%|▌ | 5/100 [00:00<00:01, 52.14 it/sec, obj=2.39e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 4.631e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:02: ... 6%|▌ | 6/100 [00:00<00:01, 52.00 it/sec, obj=3.15e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 4.166e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:02: ... 7%|▋ | 7/100 [00:00<00:01, 52.12 it/sec, obj=3.91e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.968e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:02: ... 8%|▊ | 8/100 [00:00<00:01, 52.05 it/sec, obj=4.5e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.545e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:02: ... 9%|▉ | 9/100 [00:00<00:01, 49.96 it/sec, obj=4.95e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.811e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:02: ... 10%|█ | 10/100 [00:00<00:01, 50.14 it/sec, obj=5.42e+4]
INFO - 13:53:02: ... 11%|█ | 11/100 [00:00<00:01, 51.34 it/sec, obj=1.63e+5]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.233e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:02: ... 12%|█▏ | 12/100 [00:00<00:01, 51.16 it/sec, obj=1.35e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 6.032e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:02: ... 13%|█▎ | 13/100 [00:00<00:01, 51.04 it/sec, obj=2.44e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 4.991e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:02: ... 14%|█▍ | 14/100 [00:00<00:01, 51.07 it/sec, obj=3.28e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.326e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:02: ... 15%|█▌ | 15/100 [00:00<00:01, 50.85 it/sec, obj=4.19e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.100e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:02: ... 16%|█▌ | 16/100 [00:00<00:01, 50.89 it/sec, obj=4.76e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 4.636e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:02: ... 17%|█▋ | 17/100 [00:00<00:01, 50.85 it/sec, obj=5.16e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 4.011e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:02: ... 18%|█▊ | 18/100 [00:00<00:01, 50.92 it/sec, obj=5.52e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 4.376e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:02: ... 19%|█▉ | 19/100 [00:00<00:01, 50.91 it/sec, obj=5.78e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 3.274e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:02: ... 20%|██ | 20/100 [00:00<00:01, 51.02 it/sec, obj=5.98e+4]
INFO - 13:53:02: ... 21%|██ | 21/100 [00:00<00:01, 51.61 it/sec, obj=1.63e+5]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.416e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:02: ... 22%|██▏ | 22/100 [00:00<00:01, 51.51 it/sec, obj=1.97e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 7.049e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:02: ... 23%|██▎ | 23/100 [00:00<00:01, 51.48 it/sec, obj=3.17e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 7.114e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:02: ... 24%|██▍ | 24/100 [00:00<00:01, 51.50 it/sec, obj=4.02e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 6.879e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:02: ... 25%|██▌ | 25/100 [00:00<00:01, 51.50 it/sec, obj=4.59e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 6.346e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:02: ... 26%|██▌ | 26/100 [00:00<00:01, 51.53 it/sec, obj=4.97e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.139e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 27%|██▋ | 27/100 [00:00<00:01, 51.54 it/sec, obj=5.3e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 3.088e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 28%|██▊ | 28/100 [00:00<00:01, 51.57 it/sec, obj=5.6e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.614e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 29%|██▉ | 29/100 [00:00<00:01, 51.59 it/sec, obj=5.89e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.419e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 30%|███ | 30/100 [00:00<00:01, 51.64 it/sec, obj=6.18e+4]
INFO - 13:53:03: ... 31%|███ | 31/100 [00:00<00:01, 52.03 it/sec, obj=1.63e+5]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 6.445e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 32%|███▏ | 32/100 [00:00<00:01, 52.00 it/sec, obj=2.43e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 7.489e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 33%|███▎ | 33/100 [00:00<00:01, 51.96 it/sec, obj=3.58e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 7.720e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 34%|███▍ | 34/100 [00:00<00:01, 51.95 it/sec, obj=4.29e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 7.355e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 35%|███▌ | 35/100 [00:00<00:01, 51.76 it/sec, obj=4.77e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.901e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 36%|███▌ | 36/100 [00:00<00:01, 51.76 it/sec, obj=5.12e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 4.912e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 37%|███▋ | 37/100 [00:00<00:01, 51.75 it/sec, obj=5.43e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 4.813e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 38%|███▊ | 38/100 [00:00<00:01, 51.71 it/sec, obj=5.74e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 4.575e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 39%|███▉ | 39/100 [00:00<00:01, 51.69 it/sec, obj=6.05e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 4.228e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 40%|████ | 40/100 [00:00<00:01, 51.67 it/sec, obj=6.35e+4]
INFO - 13:53:03: ... 41%|████ | 41/100 [00:00<00:01, 51.96 it/sec, obj=1.63e+5]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 7.024e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 42%|████▏ | 42/100 [00:00<00:01, 51.91 it/sec, obj=2.75e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.011e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 43%|████▎ | 43/100 [00:00<00:01, 51.86 it/sec, obj=3.82e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.113e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 44%|████▍ | 44/100 [00:00<00:01, 51.82 it/sec, obj=4.42e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 7.519e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 45%|████▌ | 45/100 [00:00<00:01, 51.75 it/sec, obj=4.9e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 6.055e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 46%|████▌ | 46/100 [00:00<00:01, 51.68 it/sec, obj=5.28e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 6.144e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 47%|████▋ | 47/100 [00:00<00:01, 51.67 it/sec, obj=5.61e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 6.279e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 48%|████▊ | 48/100 [00:00<00:01, 51.65 it/sec, obj=5.93e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 6.108e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 49%|████▉ | 49/100 [00:00<00:00, 51.64 it/sec, obj=6.24e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 7.238e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 50%|█████ | 50/100 [00:00<00:00, 51.64 it/sec, obj=6.54e+4]
INFO - 13:53:03: ... 51%|█████ | 51/100 [00:00<00:00, 51.85 it/sec, obj=1.63e+5]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 7.431e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 52%|█████▏ | 52/100 [00:01<00:00, 51.82 it/sec, obj=2.99e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.364e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 53%|█████▎ | 53/100 [00:01<00:00, 51.78 it/sec, obj=3.96e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.413e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 54%|█████▍ | 54/100 [00:01<00:00, 51.76 it/sec, obj=4.51e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 7.943e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 55%|█████▌ | 55/100 [00:01<00:00, 51.73 it/sec, obj=5e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 7.337e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 56%|█████▌ | 56/100 [00:01<00:00, 51.71 it/sec, obj=5.43e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 7.369e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 57%|█████▋ | 57/100 [00:01<00:00, 51.71 it/sec, obj=5.78e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 7.650e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 58%|█████▊ | 58/100 [00:01<00:00, 51.71 it/sec, obj=6.11e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 7.892e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 59%|█████▉ | 59/100 [00:01<00:00, 51.70 it/sec, obj=6.41e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.651e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 60%|██████ | 60/100 [00:01<00:00, 51.71 it/sec, obj=6.66e+4]
INFO - 13:53:03: ... 61%|██████ | 61/100 [00:01<00:00, 51.90 it/sec, obj=1.63e+5]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 7.740e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 62%|██████▏ | 62/100 [00:01<00:00, 51.84 it/sec, obj=3.18e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.649e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 63%|██████▎ | 63/100 [00:01<00:00, 51.81 it/sec, obj=4.07e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.844e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 64%|██████▍ | 64/100 [00:01<00:00, 51.77 it/sec, obj=4.6e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 7.984e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 65%|██████▌ | 65/100 [00:01<00:00, 51.74 it/sec, obj=5.09e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.131e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 66%|██████▌ | 66/100 [00:01<00:00, 51.72 it/sec, obj=5.53e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.602e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 67%|██████▋ | 67/100 [00:01<00:00, 51.71 it/sec, obj=5.92e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.732e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 68%|██████▊ | 68/100 [00:01<00:00, 51.68 it/sec, obj=6.25e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.134e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 69%|██████▉ | 69/100 [00:01<00:00, 51.65 it/sec, obj=6.52e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.496e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 70%|███████ | 70/100 [00:01<00:00, 51.63 it/sec, obj=6.71e+4]
INFO - 13:53:03: ... 71%|███████ | 71/100 [00:01<00:00, 51.79 it/sec, obj=1.63e+5]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.000e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 72%|███████▏ | 72/100 [00:01<00:00, 51.76 it/sec, obj=3.32e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.897e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 73%|███████▎ | 73/100 [00:01<00:00, 51.74 it/sec, obj=4.15e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.148e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 74%|███████▍ | 74/100 [00:01<00:00, 51.70 it/sec, obj=4.69e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.706e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 75%|███████▌ | 75/100 [00:01<00:00, 51.66 it/sec, obj=5.19e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.195e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 76%|███████▌ | 76/100 [00:01<00:00, 51.64 it/sec, obj=5.63e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.466e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 77%|███████▋ | 77/100 [00:01<00:00, 51.62 it/sec, obj=6.01e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.580e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:03: ... 78%|███████▊ | 78/100 [00:01<00:00, 51.60 it/sec, obj=6.32e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.258e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:04: ... 79%|███████▉ | 79/100 [00:01<00:00, 51.57 it/sec, obj=6.55e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.020e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:04: ... 80%|████████ | 80/100 [00:01<00:00, 51.56 it/sec, obj=6.72e+4]
INFO - 13:53:04: ... 81%|████████ | 81/100 [00:01<00:00, 51.71 it/sec, obj=1.63e+5]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.222e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:04: ... 82%|████████▏ | 82/100 [00:01<00:00, 51.68 it/sec, obj=3.44e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.179e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:04: ... 83%|████████▎ | 83/100 [00:01<00:00, 51.65 it/sec, obj=4.23e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.446e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:04: ... 84%|████████▍ | 84/100 [00:01<00:00, 51.61 it/sec, obj=4.78e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.507e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:04: ... 85%|████████▌ | 85/100 [00:01<00:00, 51.56 it/sec, obj=5.3e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.936e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:04: ... 86%|████████▌ | 86/100 [00:01<00:00, 51.51 it/sec, obj=5.74e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.005e+05, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:04: ... 87%|████████▋ | 87/100 [00:01<00:00, 51.47 it/sec, obj=6.09e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.010e+05, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:04: ... 88%|████████▊ | 88/100 [00:01<00:00, 51.43 it/sec, obj=6.35e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.877e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:04: ... 89%|████████▉ | 89/100 [00:01<00:00, 51.40 it/sec, obj=6.53e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.866e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:04: ... 90%|█████████ | 90/100 [00:01<00:00, 51.36 it/sec, obj=6.67e+4]
INFO - 13:53:04: ... 91%|█████████ | 91/100 [00:01<00:00, 51.47 it/sec, obj=1.63e+5]
INFO - 13:53:04: ... 92%|█████████▏| 92/100 [00:01<00:00, 51.58 it/sec, obj=6.89e+4]
INFO - 13:53:04: ... 93%|█████████▎| 93/100 [00:01<00:00, 51.71 it/sec, obj=4.03e+4]
INFO - 13:53:04: ... 94%|█████████▍| 94/100 [00:01<00:00, 51.84 it/sec, obj=2.71e+4]
INFO - 13:53:04: ... 95%|█████████▌| 95/100 [00:01<00:00, 51.97 it/sec, obj=2.07e+4]
INFO - 13:53:04: ... 96%|█████████▌| 96/100 [00:01<00:00, 52.11 it/sec, obj=1.78e+4]
INFO - 13:53:04: ... 97%|█████████▋| 97/100 [00:01<00:00, 52.23 it/sec, obj=1.68e+4]
INFO - 13:53:04: ... 98%|█████████▊| 98/100 [00:01<00:00, 52.35 it/sec, obj=1.69e+4]
INFO - 13:53:04: ... 99%|█████████▉| 99/100 [00:01<00:00, 52.47 it/sec, obj=1.76e+4]
INFO - 13:53:04: ... 100%|██████████| 100/100 [00:01<00:00, 52.60 it/sec, obj=1.87e+4]
INFO - 13:53:04: Optimization result:
INFO - 13:53:04: Optimizer info:
INFO - 13:53:04: Status: None
INFO - 13:53:04: Message: None
INFO - 13:53:04: Number of calls to the objective function by the optimizer: 100
INFO - 13:53:04: Solution:
INFO - 13:53:04: Objective: 4136.820826715568
INFO - 13:53:04: Design space:
INFO - 13:53:04: +------------------+-------------+-------------------+-------------+-------+
INFO - 13:53:04: | name | lower_bound | value | upper_bound | type |
INFO - 13:53:04: +------------------+-------------+-------------------+-------------+-------+
INFO - 13:53:04: | penalty_level | 0 | 4.444444444444445 | 40 | float |
INFO - 13:53:04: | l2_penalty_ratio | 0 | 0 | 1 | float |
INFO - 13:53:04: +------------------+-------------+-------------------+-------------+-------+
INFO - 13:53:04: *** End DOEScenario execution (time: 0:00:01.914330) ***
(4.444444444444445, 0.0, 4136.820826715568)
Get the history¶
calibration.dataset
Visualize the results¶
penalty_level = calibration.get_history("penalty_level").flatten()
l2_penalty_ratio = calibration.get_history("l2_penalty_ratio").flatten()
criterion = calibration.get_history("criterion").flatten()
learning = calibration.get_history("learning").flatten()
triang = Triangulation(penalty_level, l2_penalty_ratio)
fig = plt.figure()
ax = fig.add_subplot(1, 2, 1)
ax.tricontourf(triang, criterion, cmap="Purples")
ax.scatter(x_opt["penalty_level"][0], x_opt["l2_penalty_ratio"][0])
ax.set_xlabel("penalty level")
ax.set_ylabel("l2 penalty ratio")
ax.set_title("Test measure")
ax = fig.add_subplot(1, 2, 2)
ax.tricontourf(triang, learning, cmap="Purples")
ax.scatter(x_opt["penalty_level"][0], x_opt["l2_penalty_ratio"][0])
ax.set_xlabel("penalty level")
ax.set_ylabel("l2 penalty ratio")
ax.set_title("Learning measure")
plt.show()
Add an optimization stage¶
calibration_space = DesignSpace()
calibration_space.add_variable("penalty_level", 1, "float", 0.0, 40.0, 0.0)
calibration_space.add_variable("l2_penalty_ratio", 1, "float", 0.0, 1.0, 0.5)
calibration = MLAlgoCalibration(
"PolynomialRegressor",
dataset,
["penalty_level", "l2_penalty_ratio"],
calibration_space,
MSEMeasure,
measure_evaluation_method_name=measure_evaluation_method_name,
measure_options=measure_options,
degree=10,
)
calibration.execute({"algo": "NLOPT_COBYLA", "max_iter": 100})
x_opt2 = calibration.optimal_parameters
f_opt2 = calibration.optimal_criterion
fig = plt.figure()
ax = fig.add_subplot(1, 2, 1)
ax.tricontourf(triang, criterion, cmap="Purples")
ax.scatter(x_opt["penalty_level"][0], x_opt["l2_penalty_ratio"][0])
ax.scatter(x_opt2["penalty_level"][0], x_opt2["l2_penalty_ratio"][0], color="red")
ax.set_xlabel("penalty level")
ax.set_ylabel("l2 penalty ratio")
ax.set_title("Test measure")
ax = fig.add_subplot(1, 2, 2)
ax.tricontourf(triang, learning, cmap="Purples")
ax.scatter(x_opt["penalty_level"][0], x_opt["l2_penalty_ratio"][0])
ax.scatter(x_opt2["penalty_level"][0], x_opt2["l2_penalty_ratio"][0], color="red")
ax.set_xlabel("penalty level")
ax.set_ylabel("l2 penalty ratio")
ax.set_title("Learning measure")
plt.show()
n_iterations = len(calibration.scenario.disciplines[0].cache)
print(f"MSE with DOE: {f_opt} (100 evaluations)")
print(f"MSE with OPT: {f_opt2} ({n_iterations} evaluations)")
print(f"MSE reduction:{round((f_opt2 - f_opt) / f_opt * 100)}%")
INFO - 13:53:04:
INFO - 13:53:04: *** Start MDOScenario execution ***
INFO - 13:53:04: MDOScenario
INFO - 13:53:04: Disciplines: MLAlgoAssessor
INFO - 13:53:04: MDO formulation: DisciplinaryOpt
INFO - 13:53:04: Optimization problem:
INFO - 13:53:04: minimize criterion(penalty_level, l2_penalty_ratio)
INFO - 13:53:04: with respect to l2_penalty_ratio, penalty_level
INFO - 13:53:04: over the design space:
INFO - 13:53:04: +------------------+-------------+-------+-------------+-------+
INFO - 13:53:04: | name | lower_bound | value | upper_bound | type |
INFO - 13:53:04: +------------------+-------------+-------+-------------+-------+
INFO - 13:53:04: | penalty_level | 0 | 0 | 40 | float |
INFO - 13:53:04: | l2_penalty_ratio | 0 | 0.5 | 1 | float |
INFO - 13:53:04: +------------------+-------------+-------+-------------+-------+
INFO - 13:53:04: Solving optimization problem with algorithm NLOPT_COBYLA:
INFO - 13:53:04: ... 0%| | 0/100 [00:00<?, ?it]
INFO - 13:53:04: ... 1%| | 1/100 [00:00<00:01, 55.15 it/sec, obj=1.63e+5]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.287e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:04: ... 2%|▏ | 2/100 [00:00<00:01, 52.54 it/sec, obj=4.06e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.952e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:04: ... 3%|▎ | 3/100 [00:00<00:01, 52.00 it/sec, obj=4.28e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 7.118e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:04: ... 4%|▍ | 4/100 [00:00<00:01, 51.50 it/sec, obj=5.16e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.089e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:04: ... 5%|▌ | 5/100 [00:00<00:01, 50.94 it/sec, obj=4.66e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 7.973e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:04: ... 6%|▌ | 6/100 [00:00<00:01, 50.55 it/sec, obj=3.63e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 7.402e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:04: ... 7%|▋ | 7/100 [00:00<00:01, 50.39 it/sec, obj=3.03e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 6.059e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:04: ... 8%|▊ | 8/100 [00:00<00:01, 49.98 it/sec, obj=2.03e+4]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.428e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:04: ... 9%|▉ | 9/100 [00:00<00:01, 49.67 it/sec, obj=2.75e+3]
INFO - 13:53:04: ... 10%|█ | 10/100 [00:00<00:01, 50.27 it/sec, obj=493]
INFO - 13:53:04: ... 11%|█ | 11/100 [00:00<00:01, 51.38 it/sec, obj=1.63e+5]
INFO - 13:53:04: ... 12%|█▏ | 12/100 [00:00<00:01, 52.33 it/sec, obj=1.63e+5]
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/5.1.0/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.976e+04, tolerance: 2.850e+03
model = cd_fast.enet_coordinate_descent(
INFO - 13:53:04: ... 13%|█▎ | 13/100 [00:00<00:01, 52.06 it/sec, obj=5.23e+3]
INFO - 13:53:04: ... 14%|█▍ | 14/100 [00:00<00:01, 52.35 it/sec, obj=493]
INFO - 13:53:04: ... 15%|█▌ | 15/100 [00:00<00:01, 52.56 it/sec, obj=493]
INFO - 13:53:04: ... 16%|█▌ | 16/100 [00:00<00:01, 52.75 it/sec, obj=493]
INFO - 13:53:04: Optimization result:
INFO - 13:53:04: Optimizer info:
INFO - 13:53:04: Status: None
INFO - 13:53:04: Message: Successive iterates of the objective function are closer than ftol_rel or ftol_abs. GEMSEO Stopped the driver
INFO - 13:53:04: Number of calls to the objective function by the optimizer: 17
INFO - 13:53:04: Solution:
INFO - 13:53:04: Objective: 493.1818200496802
INFO - 13:53:04: Design space:
INFO - 13:53:04: +------------------+-------------+-----------------------+-------------+-------+
INFO - 13:53:04: | name | lower_bound | value | upper_bound | type |
INFO - 13:53:04: +------------------+-------------+-----------------------+-------------+-------+
INFO - 13:53:04: | penalty_level | 0 | 2.289834988289385e-15 | 40 | float |
INFO - 13:53:04: | l2_penalty_ratio | 0 | 0.5765298371174132 | 1 | float |
INFO - 13:53:04: +------------------+-------------+-----------------------+-------------+-------+
INFO - 13:53:04: *** End MDOScenario execution (time: 0:00:00.318244) ***
MSE with DOE: 4136.820826715568 (100 evaluations)
MSE with OPT: 493.1818200496802 (1 evaluations)
MSE reduction:-88%
Total running time of the script: (0 minutes 3.706 seconds)