Fix notebook-style examples

### Describe the issue linked to the documentation

Many legitimate notebook style examples have been broken, and specifically by the following PR
https://github.com/scikit-learn/scikit-learn/pull/9061


### List of examples to update
**Note for maintainers**: the content between begin/end_auto_generated is updated automatically by a script. If you edit it by hand your changes may be reverted. The script doing the update: https://gist.github.com/lesteve/478d52599d394ec5e7f56dbf0827a5e9

Here are all the examples that use patterns like `# #######` (found by `ag -l '# #####*\s#' examples | sort`, note there may be false positives ... for I removed [examples/impute/plot_missing_values.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/impute/plot_missing_values.py) which is using `# %%` but also `# ####` as title underlines ...):

begin_auto_generated
- [x] [examples/applications/plot_prediction_latency.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/applications/plot_prediction_latency.py) #22418
- [x] [examples/applications/plot_stock_market.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/applications/plot_stock_market.py) #22461
- [x] [examples/applications/wikipedia_principal_eigenvector.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/applications/wikipedia_principal_eigenvector.py) #22704
- [x] [examples/calibration/plot_calibration.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/calibration/plot_calibration.py) #22734
- [x] [examples/classification/plot_lda_qda.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/classification/plot_lda_qda.py) #22528
- [x] [examples/cluster/plot_affinity_propagation.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/cluster/plot_affinity_propagation.py) #22559
- [x] [examples/cluster/plot_coin_ward_segmentation.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/cluster/plot_coin_ward_segmentation.py) #23164
- [x] [examples/cluster/plot_dbscan.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/cluster/plot_dbscan.py) #22568
- [x] [examples/cluster/plot_dict_face_patches.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/cluster/plot_dict_face_patches.py) #22929
- [x] [examples/cluster/plot_feature_agglomeration_vs_univariate_selection.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/cluster/plot_feature_agglomeration_vs_univariate_selection.py) #22796
- [x] [examples/cluster/plot_mean_shift.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/cluster/plot_mean_shift.py) #22713
- [x] [examples/cluster/plot_mini_batch_kmeans.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/cluster/plot_mini_batch_kmeans.py) #22900
- [x] [examples/cluster/plot_segmentation_toy.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/cluster/plot_segmentation_toy.py) #23140
- [x] [examples/cluster/plot_ward_structured_vs_unstructured.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/cluster/plot_ward_structured_vs_unstructured.py) #23228
- [x] [examples/covariance/plot_covariance_estimation.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/covariance/plot_covariance_estimation.py) #23150
- [x] [examples/covariance/plot_sparse_cov.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/covariance/plot_sparse_cov.py) #22807
- [x] [examples/cross_decomposition/plot_compare_cross_decomposition.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/cross_decomposition/plot_compare_cross_decomposition.py) https://github.com/scikit-learn/scikit-learn/pull/23365
- [x] [examples/decomposition/plot_faces_decomposition.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/decomposition/plot_faces_decomposition.py) #22452
- [x] [examples/decomposition/plot_ica_blind_source_separation.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/decomposition/plot_ica_blind_source_separation.py) https://github.com/scikit-learn/scikit-learn/pull/23365
- [x] [examples/decomposition/plot_ica_vs_pca.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/decomposition/plot_ica_vs_pca.py) #23106
- [x] [examples/decomposition/plot_image_denoising.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/decomposition/plot_image_denoising.py) #22739
- [x] [examples/decomposition/plot_pca_3d.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/decomposition/plot_pca_3d.py) #23064
- [x] [examples/decomposition/plot_pca_vs_fa_model_selection.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/decomposition/plot_pca_vs_fa_model_selection.py) #23148
- [x] [examples/exercises/plot_cv_diabetes.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/exercises/plot_cv_diabetes.py) #22740
- [x] [examples/feature_selection/plot_feature_selection.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/feature_selection/plot_feature_selection.py) #22437
- [x] [examples/linear_model/plot_ard.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/linear_model/plot_ard.py) #22481
- [x] [examples/linear_model/plot_bayesian_ridge_curvefit.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/linear_model/plot_bayesian_ridge_curvefit.py) #22916
- [x] [examples/linear_model/plot_bayesian_ridge.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/linear_model/plot_bayesian_ridge.py) #22916 #22794
- [x] [examples/linear_model/plot_lasso_and_elasticnet.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/linear_model/plot_lasso_and_elasticnet.py) #22423
- [x] [examples/linear_model/plot_lasso_dense_vs_sparse_data.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/linear_model/plot_lasso_dense_vs_sparse_data.py) #22789
- [x] [examples/linear_model/plot_logistic_path.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/linear_model/plot_logistic_path.py) #22536
- [x] [examples/linear_model/plot_multi_task_lasso_support.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/linear_model/plot_multi_task_lasso_support.py) https://github.com/scikit-learn/scikit-learn/pull/23365
- [x] [examples/linear_model/plot_ols_3d.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/linear_model/plot_ols_3d.py) #22547
- [x] [examples/linear_model/plot_ridge_path.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/linear_model/plot_ridge_path.py) #23209
- [x] [examples/linear_model/plot_theilsen.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/linear_model/plot_theilsen.py) #23002
- [x] [examples/miscellaneous/plot_kernel_ridge_regression.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/miscellaneous/plot_kernel_ridge_regression.py) #22804
- [x] [examples/model_selection/grid_search_text_feature_extraction.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/model_selection/grid_search_text_feature_extraction.py) #22558
- [x] [examples/model_selection/plot_roc_crossval.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/model_selection/plot_roc_crossval.py) #22799
- [x] [examples/model_selection/plot_train_error_vs_test_error.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/model_selection/plot_train_error_vs_test_error.py) #22440
- [x] [examples/neighbors/plot_regression.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/neighbors/plot_regression.py) #22416
- [x] [examples/neural_networks/plot_rbm_logistic_classification.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/neural_networks/plot_rbm_logistic_classification.py) #23104
- [x] [examples/semi_supervised/plot_label_propagation_digits.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/semi_supervised/plot_label_propagation_digits.py) #22725
- [x] [examples/semi_supervised/plot_label_propagation_structure.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/semi_supervised/plot_label_propagation_structure.py) #22726
- [x] [examples/svm/plot_rbf_parameters.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/svm/plot_rbf_parameters.py) #22724
- [x] [examples/svm/plot_svm_anova.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/svm/plot_svm_anova.py) #22779
- [x] [examples/svm/plot_svm_regression.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/svm/plot_svm_regression.py) #22534
- [x] [examples/text/plot_document_clustering.py](https://github.com/scikit-learn/scikit-learn/blob/main/examples/text/plot_document_clustering.py) #22443

end_auto_generated

### Suggest a potential alternative/fix

The examples need to be reviewed on a case by case, to know whether they are "notebook-syle", as in https://sphinx-gallery.github.io/stable/tutorials/plot_parse.html#sphx-glr-tutorials-plot-parse-py or not. In general, we should favor notebook-style examples, which are typically more readable.

We should probably favor the "# %%" syntax to the long line of "###"
https://sphinx-gallery.github.io/stable/syntax.html#embed-rst-in-your-example-python-files

In terms of reviewing workflow, it can be useful to to send different PRs, rather than a big PR which will be harder to review.

### Pieces of advice if you are interested in working on this issue

- pick a file to get started with: e.g. https://github.com/scikit-learn/scikit-learn/blob/main/examples/semi_supervised/plot_label_propagation_digits.py with its [rendered HTML in the doc](https://scikit-learn.org/dev/auto_examples/semi_supervised/plot_label_propagation_digits.html)
- Mention which file you are working in a comment so that different people can work in parallel on different files
- use `# %%` as cell separator where you think it is appropriate. For example in https://github.com/scikit-learn/scikit-learn/blob/main/examples/semi_supervised/plot_label_propagation_digits.py I would say that some comments may not have their own cell like "Pick the top 10 most uncertain labels" whereas some should be turned into a title like "Plot".
- Look at existing notebook-style example for inspiration e.g. https://github.com/scikit-learn/scikit-learn/blob/main/examples/manifold/plot_swissroll.py with its [rendered HTML in the doc](https://scikit-learn.org/dev/auto_examples/manifold/plot_swissroll.html#sphx-glr-auto-examples-manifold-plot-swissroll-py)
- Look at the contributing doc to build the example HTML locally: https://scikit-learn.org/stable/developers/contributing.html in particular using `EXAMPLES_PATTERN=plot_label_propagation_digit make html` will only run the examples with `plot_label_propagation_digit` in their filenames. This makes it quicker to generate the doc for only the example you are working on and look at the HTML rendering locally.
- once you create a PR, check the CircleCI status at the bottom of the page and click on "Details"
![image](https://user-images.githubusercontent.com/1680079/153019748-e8393f78-75c6-45a4-bd53-0474d09d4ff7.png)
- It should bring you to a page like this, click on the name of the example you modify and check that the doc for this example looks right:
![image](https://user-images.githubusercontent.com/1680079/153020119-4d874be8-abff-4973-bcc2-842109be7654.png)

COMMENT:
@ss-is-master-chief I have added a "Pieces of advice if you are interested in working on this issue" section in the top post to help you (and potentially other interested people to get started). If something is not clear let us know!

Labels: Easy, Documentation, good first issue