:orphan:
.. _sphx_glr_auto_meta_modeling:
.. _Meta modeling:
Meta modeling
=============
.. raw:: html
.. _sphx_glr_auto_meta_modeling_general_purpose_metamodels:
.. _General purpose metamodels:
General purpose metamodels
--------------------------
.. raw:: html
.. only:: html
.. figure:: /auto_meta_modeling/general_purpose_metamodels/images/thumb/sphx_glr_plot_create_linear_least_squares_model_thumb.png
:alt: Create a linear least squares model
:ref:`sphx_glr_auto_meta_modeling_general_purpose_metamodels_plot_create_linear_least_squares_model.py`
.. raw:: html
.. toctree::
:hidden:
/auto_meta_modeling/general_purpose_metamodels/plot_create_linear_least_squares_model
.. raw:: html
.. only:: html
.. figure:: /auto_meta_modeling/general_purpose_metamodels/images/thumb/sphx_glr_plot_general_linear_model_thumb.png
:alt: Create a general linear model metamodel
:ref:`sphx_glr_auto_meta_modeling_general_purpose_metamodels_plot_general_linear_model.py`
.. raw:: html
.. toctree::
:hidden:
/auto_meta_modeling/general_purpose_metamodels/plot_general_linear_model
.. raw:: html
.. only:: html
.. figure:: /auto_meta_modeling/general_purpose_metamodels/images/thumb/sphx_glr_plot_taylor_approximation_thumb.png
:alt: Taylor approximations
:ref:`sphx_glr_auto_meta_modeling_general_purpose_metamodels_plot_taylor_approximation.py`
.. raw:: html
.. toctree::
:hidden:
/auto_meta_modeling/general_purpose_metamodels/plot_taylor_approximation
.. raw:: html
.. only:: html
.. figure:: /auto_meta_modeling/general_purpose_metamodels/images/thumb/sphx_glr_plot_linear_model_thumb.png
:alt: Create a linear model
:ref:`sphx_glr_auto_meta_modeling_general_purpose_metamodels_plot_linear_model.py`
.. raw:: html
.. toctree::
:hidden:
/auto_meta_modeling/general_purpose_metamodels/plot_linear_model
.. raw:: html
.. only:: html
.. figure:: /auto_meta_modeling/general_purpose_metamodels/images/thumb/sphx_glr_plot_expert_mixture_thumb.png
:alt: Mixture of experts
:ref:`sphx_glr_auto_meta_modeling_general_purpose_metamodels_plot_expert_mixture.py`
.. raw:: html
.. toctree::
:hidden:
/auto_meta_modeling/general_purpose_metamodels/plot_expert_mixture
.. raw:: html
.. only:: html
.. figure:: /auto_meta_modeling/general_purpose_metamodels/images/thumb/sphx_glr_plot_overfitting_model_selection_thumb.png
:alt: Over-fitting and model selection
:ref:`sphx_glr_auto_meta_modeling_general_purpose_metamodels_plot_overfitting_model_selection.py`
.. raw:: html
.. toctree::
:hidden:
/auto_meta_modeling/general_purpose_metamodels/plot_overfitting_model_selection
.. raw:: html
.. _sphx_glr_auto_meta_modeling_polynomial_chaos_metamodel:
.. _Polynomial chaos metamodel:
Polynomial chaos metamodel
--------------------------
.. raw:: html
.. only:: html
.. figure:: /auto_meta_modeling/polynomial_chaos_metamodel/images/thumb/sphx_glr_plot_chaos_distribution_transformation_thumb.png
:alt: Apply a transform or inverse transform on your polynomial chaos
:ref:`sphx_glr_auto_meta_modeling_polynomial_chaos_metamodel_plot_chaos_distribution_transformation.py`
.. raw:: html
.. toctree::
:hidden:
/auto_meta_modeling/polynomial_chaos_metamodel/plot_chaos_distribution_transformation
.. raw:: html
.. only:: html
.. figure:: /auto_meta_modeling/polynomial_chaos_metamodel/images/thumb/sphx_glr_plot_chaos_build_distribution_thumb.png
:alt: Fit a distribution from an input sample
:ref:`sphx_glr_auto_meta_modeling_polynomial_chaos_metamodel_plot_chaos_build_distribution.py`
.. raw:: html
.. toctree::
:hidden:
/auto_meta_modeling/polynomial_chaos_metamodel/plot_chaos_build_distribution
.. raw:: html
.. only:: html
.. figure:: /auto_meta_modeling/polynomial_chaos_metamodel/images/thumb/sphx_glr_plot_functional_chaos_exploitation_thumb.png
:alt: Polynomial chaos exploitation
:ref:`sphx_glr_auto_meta_modeling_polynomial_chaos_metamodel_plot_functional_chaos_exploitation.py`
.. raw:: html
.. toctree::
:hidden:
/auto_meta_modeling/polynomial_chaos_metamodel/plot_functional_chaos_exploitation
.. raw:: html
.. only:: html
.. figure:: /auto_meta_modeling/polynomial_chaos_metamodel/images/thumb/sphx_glr_plot_functional_chaos_database_thumb.png
:alt: Polynomial chaos over database
:ref:`sphx_glr_auto_meta_modeling_polynomial_chaos_metamodel_plot_functional_chaos_database.py`
.. raw:: html
.. toctree::
:hidden:
/auto_meta_modeling/polynomial_chaos_metamodel/plot_functional_chaos_database
.. raw:: html
.. only:: html
.. figure:: /auto_meta_modeling/polynomial_chaos_metamodel/images/thumb/sphx_glr_plot_chaos_ishigami_grouped_indices_thumb.png
:alt: Compute grouped indices for the Ishigami function
:ref:`sphx_glr_auto_meta_modeling_polynomial_chaos_metamodel_plot_chaos_ishigami_grouped_indices.py`
.. raw:: html
.. toctree::
:hidden:
/auto_meta_modeling/polynomial_chaos_metamodel/plot_chaos_ishigami_grouped_indices
.. raw:: html
.. only:: html
.. figure:: /auto_meta_modeling/polynomial_chaos_metamodel/images/thumb/sphx_glr_plot_chaos_draw_validation_thumb.png
:alt: Validate a polynomial chaos
:ref:`sphx_glr_auto_meta_modeling_polynomial_chaos_metamodel_plot_chaos_draw_validation.py`
.. raw:: html
.. toctree::
:hidden:
/auto_meta_modeling/polynomial_chaos_metamodel/plot_chaos_draw_validation
.. raw:: html
.. only:: html
.. figure:: /auto_meta_modeling/polynomial_chaos_metamodel/images/thumb/sphx_glr_plot_functional_chaos_graphs_thumb.png
:alt: Polynomial chaos graphs
:ref:`sphx_glr_auto_meta_modeling_polynomial_chaos_metamodel_plot_functional_chaos_graphs.py`
.. raw:: html
.. toctree::
:hidden:
/auto_meta_modeling/polynomial_chaos_metamodel/plot_functional_chaos_graphs
.. raw:: html
.. only:: html
.. figure:: /auto_meta_modeling/polynomial_chaos_metamodel/images/thumb/sphx_glr_plot_chaos_cantilever_beam_integration_thumb.png
:alt: Create a polynomial chaos metamodel by integration on the cantilever beam
:ref:`sphx_glr_auto_meta_modeling_polynomial_chaos_metamodel_plot_chaos_cantilever_beam_integration.py`
.. raw:: html
.. toctree::
:hidden:
/auto_meta_modeling/polynomial_chaos_metamodel/plot_chaos_cantilever_beam_integration
.. raw:: html
.. only:: html
.. figure:: /auto_meta_modeling/polynomial_chaos_metamodel/images/thumb/sphx_glr_plot_functional_chaos_advanced_ctors_thumb.png
:alt: Advanced polynomial chaos construction
:ref:`sphx_glr_auto_meta_modeling_polynomial_chaos_metamodel_plot_functional_chaos_advanced_ctors.py`
.. raw:: html
.. toctree::
:hidden:
/auto_meta_modeling/polynomial_chaos_metamodel/plot_functional_chaos_advanced_ctors
.. raw:: html
.. only:: html
.. figure:: /auto_meta_modeling/polynomial_chaos_metamodel/images/thumb/sphx_glr_plot_functional_chaos_thumb.png
:alt: Create a polynomial chaos metamodel
:ref:`sphx_glr_auto_meta_modeling_polynomial_chaos_metamodel_plot_functional_chaos.py`
.. raw:: html
.. toctree::
:hidden:
/auto_meta_modeling/polynomial_chaos_metamodel/plot_functional_chaos
.. raw:: html
.. only:: html
.. figure:: /auto_meta_modeling/polynomial_chaos_metamodel/images/thumb/sphx_glr_plot_chaos_ishigami_thumb.png
:alt: Create a polynomial chaos for the Ishigami function: a quick start guide to polynomial chaos
:ref:`sphx_glr_auto_meta_modeling_polynomial_chaos_metamodel_plot_chaos_ishigami.py`
.. raw:: html
.. toctree::
:hidden:
/auto_meta_modeling/polynomial_chaos_metamodel/plot_chaos_ishigami
.. raw:: html
.. only:: html
.. figure:: /auto_meta_modeling/polynomial_chaos_metamodel/images/thumb/sphx_glr_plot_chaos_beam_sensitivity_degree_thumb.png
:alt: Polynomial chaos is sensitive to the degree
:ref:`sphx_glr_auto_meta_modeling_polynomial_chaos_metamodel_plot_chaos_beam_sensitivity_degree.py`
.. raw:: html
.. toctree::
:hidden:
/auto_meta_modeling/polynomial_chaos_metamodel/plot_chaos_beam_sensitivity_degree
.. raw:: html
.. _sphx_glr_auto_meta_modeling_kriging_metamodel:
.. _Kriging metamodel:
Kriging metamodel
-----------------
.. raw:: html
.. only:: html
.. figure:: /auto_meta_modeling/kriging_metamodel/images/thumb/sphx_glr_plot_kriging_thumb.png
:alt: Create a metamodel using Kriging
:ref:`sphx_glr_auto_meta_modeling_kriging_metamodel_plot_kriging.py`
.. raw:: html
.. toctree::
:hidden:
/auto_meta_modeling/kriging_metamodel/plot_kriging
.. raw:: html
.. only:: html
.. figure:: /auto_meta_modeling/kriging_metamodel/images/thumb/sphx_glr_plot_kriging_cantilever_beam_thumb.png
:alt: Kriging the cantilever beam model
:ref:`sphx_glr_auto_meta_modeling_kriging_metamodel_plot_kriging_cantilever_beam.py`
.. raw:: html
.. toctree::
:hidden:
/auto_meta_modeling/kriging_metamodel/plot_kriging_cantilever_beam
.. raw:: html
.. only:: html
.. figure:: /auto_meta_modeling/kriging_metamodel/images/thumb/sphx_glr_plot_kriging_cantilever_beam_hmat_thumb.png
:alt: Kriging the cantilever beam model using HMAT
:ref:`sphx_glr_auto_meta_modeling_kriging_metamodel_plot_kriging_cantilever_beam_hmat.py`
.. raw:: html
.. toctree::
:hidden:
/auto_meta_modeling/kriging_metamodel/plot_kriging_cantilever_beam_hmat
.. raw:: html
.. only:: html
.. figure:: /auto_meta_modeling/kriging_metamodel/images/thumb/sphx_glr_plot_kriging_beam_arbitrary_trend_thumb.png
:alt: Configuring an arbitrary trend in Kriging
:ref:`sphx_glr_auto_meta_modeling_kriging_metamodel_plot_kriging_beam_arbitrary_trend.py`
.. raw:: html
.. toctree::
:hidden:
/auto_meta_modeling/kriging_metamodel/plot_kriging_beam_arbitrary_trend
.. raw:: html
.. only:: html
.. figure:: /auto_meta_modeling/kriging_metamodel/images/thumb/sphx_glr_plot_kriging_beam_trend_thumb.png
:alt: Configuring the trend in Kriging
:ref:`sphx_glr_auto_meta_modeling_kriging_metamodel_plot_kriging_beam_trend.py`
.. raw:: html
.. toctree::
:hidden:
/auto_meta_modeling/kriging_metamodel/plot_kriging_beam_trend
.. raw:: html
.. only:: html
.. figure:: /auto_meta_modeling/kriging_metamodel/images/thumb/sphx_glr_plot_kriging_simulate_thumb.png
:alt: Simulate new trajectories from a kriging metamodel
:ref:`sphx_glr_auto_meta_modeling_kriging_metamodel_plot_kriging_simulate.py`
.. raw:: html
.. toctree::
:hidden:
/auto_meta_modeling/kriging_metamodel/plot_kriging_simulate
.. raw:: html
.. only:: html
.. figure:: /auto_meta_modeling/kriging_metamodel/images/thumb/sphx_glr_plot_kriging_1D_thumb.png
:alt: Create a kriging metamodel in one dimension
:ref:`sphx_glr_auto_meta_modeling_kriging_metamodel_plot_kriging_1D.py`
.. raw:: html
.. toctree::
:hidden:
/auto_meta_modeling/kriging_metamodel/plot_kriging_1D
.. raw:: html
.. only:: html
.. figure:: /auto_meta_modeling/kriging_metamodel/images/thumb/sphx_glr_plot_kriging_hyperparameters_optimization_thumb.png
:alt: Configure the optimization solver of a kriging algorithm
:ref:`sphx_glr_auto_meta_modeling_kriging_metamodel_plot_kriging_hyperparameters_optimization.py`
.. raw:: html
.. toctree::
:hidden:
/auto_meta_modeling/kriging_metamodel/plot_kriging_hyperparameters_optimization
.. raw:: html
.. only:: html
.. figure:: /auto_meta_modeling/kriging_metamodel/images/thumb/sphx_glr_plot_kriging_sequential_thumb.png
:alt: Sequentially adding new points to a kriging
:ref:`sphx_glr_auto_meta_modeling_kriging_metamodel_plot_kriging_sequential.py`
.. raw:: html
.. toctree::
:hidden:
/auto_meta_modeling/kriging_metamodel/plot_kriging_sequential
.. raw:: html
.. only:: html
.. figure:: /auto_meta_modeling/kriging_metamodel/images/thumb/sphx_glr_plot_kriging_advanced_thumb.png
:alt: Advanced kriging
:ref:`sphx_glr_auto_meta_modeling_kriging_metamodel_plot_kriging_advanced.py`
.. raw:: html
.. toctree::
:hidden:
/auto_meta_modeling/kriging_metamodel/plot_kriging_advanced
.. raw:: html
.. _sphx_glr_auto_meta_modeling_low_rank_tensors_metamodel:
.. _Low rank tensors metamodel:
Low rank tensors metamodel
--------------------------
.. raw:: html
.. only:: html
.. figure:: /auto_meta_modeling/low_rank_tensors_metamodel/images/thumb/sphx_glr_plot_tensor_cantilever_beam_thumb.png
:alt: Tensor approximation of the cantilever beam model
:ref:`sphx_glr_auto_meta_modeling_low_rank_tensors_metamodel_plot_tensor_cantilever_beam.py`
.. raw:: html
.. toctree::
:hidden:
/auto_meta_modeling/low_rank_tensors_metamodel/plot_tensor_cantilever_beam
.. raw:: html
.. _sphx_glr_auto_meta_modeling_fields_metamodels:
.. _Fields metamodels:
Fields metamodels
-----------------
.. raw:: html
.. only:: html
.. figure:: /auto_meta_modeling/fields_metamodels/images/thumb/sphx_glr_plot_viscous_fall_metamodel_thumb.png
:alt: Viscous free fall: metamodel of a field function
:ref:`sphx_glr_auto_meta_modeling_fields_metamodels_plot_viscous_fall_metamodel.py`
.. raw:: html
.. toctree::
:hidden:
/auto_meta_modeling/fields_metamodels/plot_viscous_fall_metamodel
.. raw:: html
.. only:: html
.. figure:: /auto_meta_modeling/fields_metamodels/images/thumb/sphx_glr_plot_fieldfunction_metamodel_thumb.png
:alt: Metamodel of a field function
:ref:`sphx_glr_auto_meta_modeling_fields_metamodels_plot_fieldfunction_metamodel.py`
.. raw:: html
.. toctree::
:hidden:
/auto_meta_modeling/fields_metamodels/plot_fieldfunction_metamodel
.. raw:: html
.. only :: html
.. container:: sphx-glr-footer
:class: sphx-glr-footer-gallery
.. container:: sphx-glr-download sphx-glr-download-python
:download:`Download all examples in Python source code: auto_meta_modeling_python.zip `
.. container:: sphx-glr-download sphx-glr-download-jupyter
:download:`Download all examples in Jupyter notebooks: auto_meta_modeling_jupyter.zip `
.. only:: html
.. rst-class:: sphx-glr-signature
`Gallery generated by Sphinx-Gallery `_