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merged 7 commits into from
Sep 11, 2023
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DOC take Examples out of a dropdown #27034

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2eceb23
Update svm.rst
hiramatsuyuusuke Aug 8, 2023
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Merge branch 'scikit-learn:main' into sklearn_DD_test
hiramatsuyuusuke Aug 8, 2023
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Merge branch 'scikit-learn:main' into sklearn_DD_test
hiramatsuyuusuke Aug 8, 2023
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Merge branch 'scikit-learn:main' into sklearn_DD_test
hiramatsuyuusuke Aug 8, 2023
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Merge branch 'main' into sklearn_DD_test
hiramatsuyuusuke Aug 8, 2023
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Merge branch 'scikit-learn:main' into sklearn_DD_test
hiramatsuyuusuke Aug 18, 2023
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hiramatsuyuusuke Aug 18, 2023
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24 changes: 14 additions & 10 deletions doc/modules/svm.rst
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Expand Up @@ -521,9 +521,8 @@ is advised to use :class:`~sklearn.model_selection.GridSearchCV` with
* :ref:`sphx_glr_auto_examples_svm_plot_rbf_parameters.py`
* :ref:`sphx_glr_auto_examples_svm_plot_svm_nonlinear.py`

|details-start|
**Custom Kernels**
|details-split|
Custom Kernels
--------------

You can define your own kernels by either giving the kernel as a
python function or by precomputing the Gram matrix.
Expand All @@ -539,8 +538,9 @@ classifiers, except that:
use of ``fit()`` and ``predict()`` you will have unexpected results.


Using Python functions as kernels
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
|details-start|
**Using Python functions as kernels**
|details-split|

You can use your own defined kernels by passing a function to the
``kernel`` parameter.
Expand All @@ -558,13 +558,13 @@ instance that will use that kernel::
... return np.dot(X, Y.T)
...
>>> clf = svm.SVC(kernel=my_kernel)

|details-end|

.. topic:: Examples:

* :ref:`sphx_glr_auto_examples_svm_plot_custom_kernel.py`.

Using the Gram matrix
~~~~~~~~~~~~~~~~~~~~~
|details-start|
**Using the Gram matrix**
|details-split|

You can pass pre-computed kernels by using the ``kernel='precomputed'``
option. You should then pass Gram matrix instead of X to the `fit` and
Expand All @@ -589,6 +589,10 @@ test vectors must be provided:

|details-end|

.. topic:: Examples:

* :ref:`sphx_glr_auto_examples_svm_plot_custom_kernel.py`.

.. _svm_mathematical_formulation:

Mathematical formulation
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