Guillaume Lemaitre

Issue with the `RidgeCV` diagram representation with non-default alphas

1

It seems that we introduced a regression in the HTML representation. The following code is failing: ```python import numpy as np from sklearn.linear_model import RidgeCV RidgeCV(np.logspace(-3, 3, num=10) ``` leads...

Make `_check_n_features` and `_check_feature_names` public

7

Since we are moving, `_check_n_features` and `_check_feature_names` into a new module, I'm wondering if we should make them public as well. I can imagine some people that don't want to...

DOC merging the examples related to OPTICS, DBSCAN, and HDBSCAN

3

As stated in https://github.com/scikit-learn/scikit-learn/issues/27151, it would be great to reduce the number of examples in the gallery. Right now, we have three examples for: - OPTICS: https://scikit-learn.org/dev/auto_examples/cluster/plot_optics.html#sphx-glr-auto-examples-cluster-plot-optics-py - DBSCAN: https://scikit-learn.org/dev/auto_examples/cluster/plot_dbscan.html#sphx-glr-auto-examples-cluster-plot-dbscan-py...

ENH add a call_context parameter to Parallel to make it possible to propagate runtime configuration to the workers

4

This PR allows to call some context manager before calling the function in the parallel context. It provides the following functionalities: - add `call_context` in `Parallel` to pass a list...

TableReport column associations and tables with few rows

3

I got kind of surprise when I did the following display ```python import skrub from sklearn.datasets import fetch_california_housing skrub.patch_display() X, y = fetch_california_housing(return_X_y=True, as_frame=True) X.head() ```  It took some...

Improve rendering of matplotlib image in dark mode

1

In dark mode, the text below figure is really close of the bottom of the figure. I think that we can change our css with a little trick: ``` /*...

Passing `return_indices=True` to `skrub.cross_validate` raise an error

4

Passing the option `return_indices=True` in `skrub.cross_validate` raises an error: ```python import skrub from sklearn.datasets import make_classification from sklearn.linear_model import LogisticRegression X_a, y_a = make_classification(random_state=0) X, y = skrub.X(X_a), skrub.y(y_a) log_reg...