DOC add links to examples/linear_model/plot_elastic_net_precomputed_g…

…ram_matrix_with_weighted_samples.py (#28895)

Co-authored-by: bivav <bivavraj@gmail.com>

doc/modules/linear_model.rst

@@ -530,6 +530,7 @@ The class :class:`ElasticNetCV` can be used to set the parameters
 
   * :ref:`sphx_glr_auto_examples_linear_model_plot_lasso_and_elasticnet.py`
   * :ref:`sphx_glr_auto_examples_linear_model_plot_lasso_coordinate_descent_path.py`
+  * :ref:`sphx_glr_auto_examples_linear_model_plot_elastic_net_precomputed_gram_matrix_with_weighted_samples.py`
 
 |details-start|
 **References**

sklearn/linear_model/_coordinate_descent.py

@@ -776,6 +776,9 @@ class ElasticNet(MultiOutputMixin, RegressorMixin, LinearModel):
         Whether to use a precomputed Gram matrix to speed up
         calculations. The Gram matrix can also be passed as argument.
         For sparse input this option is always ``False`` to preserve sparsity.
+        Check :ref:`an example on how to use a precomputed Gram Matrix in ElasticNet
+        <sphx_glr_auto_examples_linear_model_plot_elastic_net_precomputed_gram_matrix_with_weighted_samples.py>`
+        for details.
 
     max_iter : int, default=1000
         The maximum number of iterations.