Feature Request - Parallel Coordinates Plot for GridSearch result analysis

### Describe the workflow you want to enable

GridSearch result are hard to analyze expecially when `param_grid` is very large.

The current documentation show usages of:
- [matrix_plot/pivot](https://scikit-learn.org/stable/_images/sphx_glr_plot_successive_halving_heatmap_001.png). That can visualize the relationship beetween 2 params for 1 metrics (2D).
- [line plot](https://scikit-learn.org/stable/_images/sphx_glr_plot_multi_metric_evaluation_001.png). Each line represent a 1D (1 params vs 1 metrics) relationship and by taking multiple line when can visualize at least 2D relationship, but this became mess for more.
- [box plot](https://scikit-learn.org/stable/_images/sphx_glr_plot_compare_reduction_001.png). Same conclusion as for line plot but using box instead.

None of these plot can represent nicely more then a 2D relationship. 3D, 4D and more can be visualize by making a bunch of basic 2D plot, but the number plot will easily became huge and we lost relationship beetween some `params`. This get even worse with `RandomizedSearchCV` as the params are not evenly compute.

One common way to represent N-D relationship without loss is to use **Parallel Coordinates Plot**:

![Example of Parallel Coordinates Plot of the proposed implementation](https://user-images.githubusercontent.com/11278197/187024865-d6183eac-8cac-45fd-a629-2a2e84daffe2.png)

The current implementation of PC Plot are:
- [Plotly express](https://plotly.com/python/parallel-coordinates-plot/). But it don't integrate well with the `param_grid` format. Plus is not matplotlib compatible.
- Tensorboard and deep learning experiement tracker (wandb ...). Same don't integrate weel, not matplotlib stack and need even more conversion work and a web server (or cloud account :()
- Handmade matplotlib implementation. Matplotlib compatible, but at the time we don't have any easy to use implementation from common package. + with `param_grid` format compatibility.

### Describe your proposed solution

I presently use my own implementation of matplotlib PC Plot (see the image above) for my work.
The current interface is:
```python
def plot_parallel_coordinates(
        grid_model: GridSearchCV, 
        params: list[str] = ["params"],
        scoring: str = ["mean_test_score"]
        cmap : Optional[str] = None,
        ax: Optional[plt.Axes] = None) -> plt.Axes
```

If think the community could benefith from using a common and scikit-learn integrated implementation (for example in `metrics.ParallelCoordinatesPlot` or `inspection.ParallelCoordinatesPlot` and with `plot_parallel_coordinates` function)

### Describe alternatives you've considered, if relevant

_No response_

### Additional context

Please give 👍 if you think this could be benefith, so we can start discuss implementation.

COMMENT:
Hi @thomasjpfan, I'm happy to ear news !
The PR https://github.com/scikit-learn/scikit-learn/pull/23740 has [an example](https://output.circle-artifacts.com/output/job/8735e9ab-a82e-4503-8715-ba42ed222f88/artifacts/0/doc/auto_examples/model_selection/plot_grid_search_text_feature_extraction.html) is excellent  solution. However it's still plotly. I wanted to make a matplotlib solution at the first place, because it's way more in "sklearn" philosophy (as far as I know). And intergrate well with current workflow, like making a multiple matplotlib axes and then passing them out in differents function arguments. 

> For me, I think parallel coordinate plots work well only if it is interactive, which means depending on a library such as plotly. A matplotlib version would work within scikit-learn's current constraints, but it creates a static image. There are ways to make [matplotlib interactive](https://matplotlib.org/stable/users/explain/interactive.html?highlight=interactive), but it only works for specific backends.

I agree with you, in this case interactivity help a lot. But even as a static image parallel plot could be extensivily usefull. I'm not a big fan ether of using matplotlib interactive backends.

Anyway in case of increasing interest, I have some code snippet for that and I will be quite happy to help with this issues ;)

Labels: New Feature, module:inspection, Needs Decision - Include Feature