Add links to examples from the docstrings and user guides

We have a rich set of examples covering a very broad range of issues, but they're not necessarily easily discoverable via the section on the bottom of the API pages.

This meta-issue is to keep track of the examples for which we've already included links in the docs, and to fix the rest.

An example of how to include links to examples in API docs and the user guide can be found here: https://github.com/scikit-learn/scikit-learn/pull/26926 . Please see how it can be done before claiming an example.

For each example, please check if it's already included in the docs, either user guides or API docs, and if not, claim it by leaving a comment at the bottom of this issue and open a pull request for it. You can open one PR for more than one example if they're very related.

Note that not all examples need to be included in this project. For instance, if an example is only a usage example, and putting a link to it doesn't add much for the users, then we can ignore it (please do leave a comment if this is your finding). Also, not all examples are in a good shape, and in your PR you can also improve the example itself.

**How to create a link to an example?**
To create a link to the example `examples/developing_estimators/sklearn_is_fitted.py`, you can write:

```
:ref:`sphx_glr_auto_examples_developing_estimators_sklearn_is_fitted.py`
```
which would automatically create the link. Notice the pattern where slashes (`/`) are converted to an underscore (`_`) and the `sphx_glr_auto_` prefix.

__IMPORTANT__: Please limit your pull requests to a limited scope, single or two classes, or a single example so that it can be reviewed easily.

Here's a list of all examples:

- examples/applications:
  - [ ] plot_cyclical_feature_engineering.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26971
  - [ ] plot_digits_denoising.py
    - [ ] https://github.com/scikit-learn/scikit-learn/pull/28929
  - [ ] plot_face_recognition.py
    - [ ] https://github.com/scikit-learn/scikit-learn/pull/29049
  - [ ] plot_model_complexity_influence.py
  - [ ] plot_outlier_detection_wine.py
    - [ ] https://github.com/scikit-learn/scikit-learn/pull/29237
  - [ ] plot_out_of_core_classification.py
  - [ ] plot_prediction_latency.py
  - [ ] plot_species_distribution_modeling.py
  - [ ] plot_stock_market.py
  - [ ] plot_tomography_l1_reconstruction.py
  - [ ] plot_topics_extraction_with_nmf_lda.py
  - [ ] wikipedia_principal_eigenvector.py

- examples/bicluster:
  - [ ] plot_bicluster_newsgroups.py
  - [ ] plot_spectral_biclustering.py
    - [ ] https://github.com/scikit-learn/scikit-learn/pull/29311
  - [ ] plot_spectral_coclustering.py
     - [ ] https://github.com/scikit-learn/scikit-learn/pull/29606

- examples/calibration:
  - [ ] plot_calibration_curve.py
  - [ ] plot_calibration_multiclass.py
  - [ ] plot_calibration.py
  - [ ] plot_compare_calibration.py

- examples/classification:
  - [ ] plot_classification_probability.py
  - [ ] plot_classifier_comparison.py
  - [ ] plot_digits_classification.py
  - [ ] plot_lda.py
      - [ ] https://github.com/scikit-learn/scikit-learn/pull/28611
  - [ ] plot_lda_qda.py
      - [ ] https://github.com/scikit-learn/scikit-learn/pull/28611

- examples/cluster:
  - [ ] plot_adjusted_for_chance_measures.py
  - [ ] plot_affinity_propagation.py
  - [ ] plot_agglomerative_clustering_metrics.py
  - [ ] plot_agglomerative_clustering.py
    - [ ] https://github.com/scikit-learn/scikit-learn/pull/28922
  - [ ] plot_agglomerative_dendrogram.py
      - [ ] https://github.com/scikit-learn/scikit-learn/pull/28885
  - [ ] plot_birch_vs_minibatchkmeans.py
    - [ ] Done
  - [ ] plot_bisect_kmeans.py
  - [ ] plot_cluster_comparison.py
  - [ ] plot_cluster_iris.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/27799
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26974
  - [ ] plot_coin_segmentation.py
  - [ ] plot_coin_ward_segmentation.py
  - [ ] plot_color_quantization.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/27799
  - [ ] plot_dbscan.py
  - [ ] plot_dict_face_patches.py
  - [ ] plot_digits_agglomeration.py
  - [ ] plot_digits_linkage.py
  - [ ] plot_face_compress.py
  - [ ] plot_feature_agglomeration_vs_univariate_selection.py
  - [ ] plot_hdbscan.py
    - [ ] Done!
  - [ ] plot_inductive_clustering.py
  - [ ] plot_kmeans_assumptions.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/27799
  - [ ] plot_kmeans_digits.py
      - [ ] https://github.com/scikit-learn/scikit-learn/pull/26981
      - [ ] https://github.com/scikit-learn/scikit-learn/pull/27799
  - [ ] plot_kmeans_plusplus.py
    - [ ] https://github.com/scikit-learn/scikit-learn/pull/30126
  - [ ] plot_kmeans_silhouette_analysis.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/27799
  - [ ] plot_kmeans_stability_low_dim_dense.py
    - [ ] https://github.com/scikit-learn/scikit-learn/pull/30349
  - [ ] plot_linkage_comparison.py
      - [ ] https://github.com/scikit-learn/scikit-learn/pull/28885
  - [ ] plot_mean_shift.py
  - [ ] plot_mini_batch_kmeans.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/27799
  - [ ] plot_optics.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26970
  - [ ] plot_segmentation_toy.py
  - [ ] plot_ward_structured_vs_unstructured.py

- examples/compose:
  - [ ] plot_column_transformer_mixed_types.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26904
  - [ ] plot_column_transformer.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26904
  - [ ] plot_compare_reduction.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26904
  - [ ] plot_digits_pipe.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26904
  - [ ] plot_feature_union.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26904
  - [ ] plot_transformed_target.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26904

- examples/covariance:
  - [ ] plot_covariance_estimation.py
  - [ ] plot_lw_vs_oas.py
    - [ ] https://github.com/scikit-learn/scikit-learn/pull/30577
  - [ ] plot_mahalanobis_distances.py
  - [ ] plot_robust_vs_empirical_covariance.py
  - [ ] plot_sparse_cov.py

- examples/cross_decomposition:
  - [ ] plot_compare_cross_decomposition.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26966
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26934
  - [ ] plot_pcr_vs_pls.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26934

- examples/datasets:
  - [ ] plot_digits_last_image.py
  - [ ] plot_iris_dataset.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26973
  - [ ] plot_random_dataset.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/27056
  - [ ] plot_random_multilabel_dataset.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/27517

- examples/decomposition:
  - [ ] plot_faces_decomposition.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26932
  - [ ] plot_ica_blind_source_separation.py
  - [ ] plot_ica_vs_pca.py
  - [ ] plot_image_denoising.py
  - [ ] plot_incremental_pca.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26932
  - [ ] plot_kernel_pca.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26932
  - [ ] plot_pca_3d.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26932
  - [ ] plot_pca_iris.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26932
  - [ ] plot_pca_vs_fa_model_selection.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26932
  - [ ] plot_pca_vs_lda.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26932
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/28611
  - [ ] plot_sparse_coding.py
  - [ ] plot_varimax_fa.py

- examples/developing_estimators:
  - [ ] sklearn_is_fitted.py: https://github.com/scikit-learn/scikit-learn/pull/26926

- examples/ensemble:
  - [ ] plot_adaboost_multiclass.py
      - [ ] https://github.com/scikit-learn/scikit-learn/pull/27913
  - [ ] plot_adaboost_regression.py
    - [ ] https://github.com/scikit-learn/scikit-learn/pull/28997
  - [ ] plot_adaboost_twoclass.py
    - [ ] https://github.com/scikit-learn/scikit-learn/pull/29023
  - [ ] plot_bias_variance.py
  - [ ] plot_ensemble_oob.py
  - [ ] plot_feature_transformation.py
  - [ ] plot_forest_hist_grad_boosting_comparison.py
  - [ ] plot_forest_importances_faces.py
  - [ ] plot_forest_importances.py
  - [ ] plot_forest_iris.py
  - [ ] plot_gradient_boosting_categorical.py
  - [ ] plot_gradient_boosting_early_stopping.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/27025
  - [ ] plot_gradient_boosting_oob.py
  - [ ] plot_gradient_boosting_quantile.py
  - [ ] plot_gradient_boosting_regression.py
    - [ ] https://github.com/scikit-learn/scikit-learn/pull/29058
  - [ ] plot_gradient_boosting_regularization.py
  - [ ] plot_isolation_forest.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26975
  - [ ] plot_monotonic_constraints.py
  - [ ] plot_random_forest_embedding.py
    - [ ] https://github.com/scikit-learn/scikit-learn/pull/30418
  - [ ] plot_random_forest_regression_multioutput.py
  - [ ] plot_stack_predictors.py
  - [ ] plot_voting_decision_regions.py
  - [ ] plot_voting_probas.py
  - [ ] plot_voting_regressor.py
    - [ ] https://github.com/scikit-learn/scikit-learn/pull/29724

- examples/exercises:
  - [ ] plot_cv_diabetes.py
  - [ ] plot_cv_digits.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/28073
  - [ ] plot_digits_classification_exercise.py
  - [ ] plot_iris_exercise.py

- examples/feature_selection:
  - [ ] plot_feature_selection_pipeline.py
  - [ ] plot_feature_selection.py
  - [ ] plot_f_test_vs_mi.py
  - [ ] plot_rfe_digits.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26950
  - [ ] plot_rfe_with_cross_validation.py
  - [ ] plot_select_from_model_diabetes.py

- examples/gaussian_process:
  - [ ] plot_compare_gpr_krr.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26980
  - [ ] plot_gpc_iris.py
  - [ ] plot_gpc_isoprobability.py
  - [ ] plot_gpc.py
  - [ ] plot_gpc_xor.py
  - [ ] plot_gpr_co2.py
  - [ ] plot_gpr_noisy.py
  - [ ] plot_gpr_noisy_targets.py
  - [ ] plot_gpr_on_structured_data.py
  - [ ] plot_gpr_prior_posterior.py

- examples/impute:
  - [ ] plot_iterative_imputer_variants_comparison.py
	  - [ ] #27053
  - [ ] plot_missing_values.py
	  - [ ] #27053

- examples/inspection:
  - [ ] plot_causal_interpretation.py
  - [ ] plot_linear_model_coefficient_interpretation.py
  - [ ] plot_partial_dependence.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/27156
  - [ ] plot_permutation_importance_multicollinear.py
  - [ ] plot_permutation_importance.py

- examples/kernel_approximation:
  - [ ] plot_scalable_poly_kernels.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/27527

- examples/linear_model:
  - [ ] plot_ard.py
  - [ ] plot_bayesian_ridge_curvefit.py
  - [ ] plot_elastic_net_precomputed_gram_matrix_with_weighted_samples.py
      - [ ] https://github.com/scikit-learn/scikit-learn/pull/28895/files
  - [ ] plot_huber_vs_ridge.py
  - [ ] plot_iris_logistic.py
  - [ ] plot_lasso_and_elasticnet.py
  - [ ] plot_lasso_coordinate_descent_path.py
  - [ ] plot_lasso_dense_vs_sparse_data.py
  - [ ] plot_lasso_lars_ic.py
  - [ ] plot_lasso_lars.py
  - [ ] plot_lasso_model_selection.py
  - [ ] plot_logistic_l1_l2_sparsity.py
  - [ ] plot_logistic_multinomial.py
  - [ ] plot_logistic_path.py
  - [ ] plot_logistic.py
  - [ ] plot_multi_task_lasso_support.py
  - [ ] plot_nnls.py
  - [ ] plot_ols_3d.py
  - [ ] plot_ols.py
  - [ ] plot_ols_ridge_variance.py
  - [ ] plot_omp.py
  - [ ] plot_poisson_regression_non_normal_loss.py
  - [ ] plot_polynomial_interpolation.py
  - [ ] plot_quantile_regression.py
  - [ ] plot_ransac.py
    - [ ] https://github.com/scikit-learn/scikit-learn/pull/29636
  - [ ] plot_ridge_coeffs.py
  - [ ] plot_ridge_path.py
  - [ ] plot_robust_fit.py
  - [ ] plot_sgd_comparison.py
  - [ ] plot_sgd_early_stopping.py
  - [ ] plot_sgd_iris.py
  - [ ] plot_sgd_loss_functions.py
  - [ ] plot_sgdocsvm_vs_ocsvm.py
  - [ ] plot_sgd_penalties.py
  - [ ] plot_sgd_separating_hyperplane.py
  - [ ] plot_sgd_weighted_samples.py
  - [ ] plot_sparse_logistic_regression_20newsgroups.py
  - [ ] plot_sparse_logistic_regression_mnist.py
  - [ ] plot_theilsen.py
  - [ ] plot_tweedie_regression_insurance_claims.py

- examples/manifold:
  - [ ] plot_compare_methods.py
    - [ ] https://github.com/scikit-learn/scikit-learn/pull/29714
  - [ ] plot_lle_digits.py
  - [ ] plot_manifold_sphere.py
  - [ ] plot_mds.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/27599
  - [ ] plot_swissroll.py
  - [ ] plot_t_sne_perplexity.py

- examples/miscellaneous:
  - [ ] plot_anomaly_comparison.py
  - [ ] plot_display_object_visualization.py
  - [ ] plot_estimator_representation.py
  - [ ] plot_isotonic_regression.py
      - [ ] https://github.com/scikit-learn/scikit-learn/pull/28673
  - [ ] plot_johnson_lindenstrauss_bound.py
  - [ ] plot_kernel_approximation.py
  - [ ] plot_kernel_ridge_regression.py
  - [ ] plot_metadata_routing.py
  - [ ] plot_multilabel.py
  - [ ] plot_multioutput_face_completion.py
  - [ ] plot_outlier_detection_bench.py
  - [ ] plot_partial_dependence_visualization_api.py
  - [ ] plot_pipeline_display.py
  - [ ] plot_roc_curve_visualization_api.py
  - [ ] plot_set_output.py

- examples/mixture:
  - [ ] plot_concentration_prior.py
  - [ ] plot_gmm_covariances.py
  - [ ] plot_gmm_init.py
  - [ ] plot_gmm_pdf.py
  - [ ] plot_gmm.py
  - [ ] plot_gmm_selection.py
  - [ ] plot_gmm_sin.py

- examples/model_selection:
  - [ ] plot_confusion_matrix.py
  - [ ] plot_cv_indices.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/27244
  - [ ] plot_cv_predict.py
  - [ ] plot_det.py
  - [ ] plot_grid_search_digits.py
  - [ ] plot_grid_search_refit_callable.py
  - [ ] plot_grid_search_stats.py
  - [ ] plot_grid_search_text_feature_extraction.py
  - [ ] plot_learning_curve.py
  - [ ] plot_likelihood_ratios.py
  - [ ] plot_multi_metric_evaluation.py
  - [ ] plot_nested_cross_validation_iris.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/28073
  - [ ] plot_permutation_tests_for_classification.py
  - [ ] plot_precision_recall.py
  - [ ] plot_randomized_search.py
  - [ ] plot_roc_crossval.py
  - [ ] plot_roc.py
  - [ ] plot_successive_halving_heatmap.py
  - [ ] plot_successive_halving_iterations.py
  - [ ] plot_train_error_vs_test_error.py
  - [ ] plot_underfitting_overfitting.py
  - [ ] plot_validation_curve.py

- examples/multioutput:
  - [ ] plot_classifier_chain_yeast.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26937

- examples/neighbors:
  - [ ] approximate_nearest_neighbors.py
  - [ ] plot_caching_nearest_neighbors.py
    - [ ] https://github.com/scikit-learn/scikit-learn/pull/30421
  - [ ] plot_classification.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26979
  - [ ] plot_digits_kde_sampling.py
  - [ ] plot_kde_1d.py
  - [ ] plot_lof_novelty_detection.py
  - [ ] plot_lof_outlier_detection.py
  - [ ] plot_nca_classification.py
  - [ ] plot_nca_dim_reduction.py
  - [ ] plot_nca_illustration.py
  - [ ] plot_nearest_centroid.py
    - [ ] https://github.com/scikit-learn/scikit-learn/pull/28984
  - [ ] plot_regression.py
    - [ ] https://github.com/scikit-learn/scikit-learn/pull/29232
  - [ ] plot_species_kde.py

- examples/neural_networks:
  - [ ] plot_mlp_alpha.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26935
  - [ ] plot_mlp_training_curves.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26935
  - [ ] plot_mnist_filters.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26935
  - [ ] plot_rbm_logistic_classification.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26935

- examples/preprocessing:
  - [ ] plot_all_scaling.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26877
  - [ ] plot_discretization_classification.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26877
  - [ ] plot_discretization.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26877
  - [ ] plot_discretization_strategies.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26877
  - [ ] plot_map_data_to_normal.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26877
  - [ ] plot_scaling_importance.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26877
  - [ ] plot_target_encoder_cross_val.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26877
  - [ ] plot_target_encoder.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26877

- examples/semi_supervised:
  - [ ] plot_label_propagation_digits_active_learning.py
  - [ ] plot_label_propagation_digits.py
  - [ ] plot_label_propagation_structure.py
  - [ ] plot_self_training_varying_threshold.py
  - [ ] plot_semi_supervised_newsgroups.py
  - [ ] plot_semi_supervised_versus_svm_iris.py

- examples/svm:
  - [ ] plot_custom_kernel.py
  - [ ] plot_iris_svc.py
  - [ ] plot_linearsvc_support_vectors.py
  - [ ] plot_oneclass.py
  - [ ] plot_rbf_parameters.py
  - [ ] plot_separating_hyperplane.py
  - [ ] plot_separating_hyperplane_unbalanced.py
  - [ ] plot_svm_anova.py
  - [ ] plot_svm_kernels.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26805
  - [ ] plot_svm_margin.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26969
  - [ ] plot_svm_nonlinear.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26972
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/27108
  - [ ] plot_svm_regression.py
  - [ ] plot_svm_scale_c.py
          - [ ] https://github.com/scikit-learn/scikit-learn/pull/28830
  - [ ] plot_svm_tie_breaking.py
    - [ ] https://github.com/scikit-learn/scikit-learn/pull/29976
  - [ ] plot_weighted_samples.py

- examples/text:
  - [ ] plot_document_classification_20newsgroups.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26938
  - [ ] plot_document_clustering.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26951
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/27799
  - [ ] plot_hashing_vs_dict_vectorizer.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26967

- examples/tree:
  - [ ] plot_cost_complexity_pruning.py
    - [ ] https://github.com/scikit-learn/scikit-learn/pull/29871
  - [ ] plot_iris_dtc.py
  - [ ] plot_tree_regression_multioutput.py
  - [ ] plot_tree_regression.py
	  - [ ] https://github.com/scikit-learn/scikit-learn/pull/26962
  - [ ] plot_unveil_tree_structure.py

COMMENT:
PR #26877 ([DOC Add links to preprocessing examples in docstrings and userguide](https://github.com/scikit-learn/scikit-learn/pull/26877)) takes care of

examples/preprocessing:

plot_all_scaling.py
plot_discretization_classification.py
plot_discretization.py
plot_discretization_strategies.py
plot_map_data_to_normal.py
plot_scaling_importance.py
plot_target_encoder_cross_val.py
plot_target_encoder.py

Labels: Documentation, Sprint, good first issue, Meta-issue