Blog post "Enhancing user experience through interactive inspection" (#221)

Author: DeaMariaLeon

_posts/2026-01-06-enhancing-user-experience.md

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+---
+title: "Enhancing user experience through interactive inspection"
+date: January 6, 2026
+
+#### Post Category and Tags ####
+# Format in titlecase without dashes (Ex. "Open Source" instead of "open-source")
+categories:
+  - Updates
+tags:
+  - Open Source
+  - Funding
+  - Diversity
+  - Machine Learning
+featured-image: sklearn_czi.png
+
+#### Author Info ####
+# Can accomodate multiple authors
+# Add SQUARE Author Image to /assets/images/author_images/ folder
+postauthors:
+  - name: Dea María Léon
+    website: https://deamarialeon.com
+    email: deamarialeon@gmail.com
+    image: dea-leon.png
+---
+<div>
+  <img src="/assets/images/posts_images/{{ page.featured-image }}" alt="">
+  {% include postauthor.html %}
+</div>
+
+
+User experience (UX) has always been an important focus for `scikit-learn`. 
+As we know, UX encompasses many aspects, but here we will focus specifically on 
+how easy it is for the user to understand `scikit-learn` models during development, 
+especially while using tools like jupyter notebooks. 
+
+## First visualizations
+ 
+Initial work to allow users to inspect their models interactively began in 2019, 
+when Thomas J. Fan introduced HTML visualizations for estimators. 
+He continued to build on this foundation with additional improvements 
+in subsequent contributions.
+
+## Lack of resources to go forward
+
+In June 2023, [issue 26595 was opened by Gaël Varoquaux](https://github.com/
+scikit-learn/scikit-learn/issues/26595) outlining several potential enhancements 
+to the HTML displays. These ideas stemmed from direct interactions with users, 
+which clearly highlighted the need for further work in this area. 
+Unfortunately, due to a lack of resources, the issue remained open for 
+approximately a year and a half.
+
+##  Wellcome grant awarded to `scikit-learn` 
+
+This was until the end of 2023, when Guillaume Lemaitre applied for a grant with
+the help of NumFOCUS, that the broader topic of Predictive model evaluation and 
+inspection was formalized. Enhancing user experience through interactive inspection 
+is an essential part of this effort and falls within the scope of the grant.
+
+The grant was awarded to `scikit-learn`and it is from the Chan Zuckerberg 
+Initiative (CZI) through its Essential Open-Source Software for Science 
+(EOSS) program. It is funded by The Wellcome Trust and administered by NumFOCUS. 
+Thanks to this financial support, work is well underway. And several objectives
+from the said issue have already been completed. 
+[See the grant application here.](https://github.com/scikit-learn/
+administrative/blob/master/czi_eoss_proposal/EOSS6-0000000551_202312181059.pdf)
+
+## First milestone: Added interactive parameters table for each element 
+
+The first milestone was introduced in`scikit-learn` version 1.7, released in 
+June 2025. A parameters table was added to the HTML representation of models, 
+displaying parameter names and their corresponding values. 
+Non-default parameters—those explicitly set by the user—are highlighted. 
+In addition, a copy-to-clipboard button is available for each parameter name. 
+The parameter name that is copied to the clipboard is the fully classified name, 
+which is shown on hover as well. The parameters table is collapsed by default 
+and can be opened by the user. 
+
+The following two images show a pipeline table before and after the milestone.
+
+<figure>
+<img src="/assets/images/posts_images/enhancing-UX/before1_7.png"
+alt="HTML visualization before scikit-learn 1.7" />
+<figcaption>
+HTML visualization before scikit-learn version 1.7
+</figcaption>
+</figure>
+
+<figure>
+<img src="/assets/images/posts_images/enhancing-UX/scikit-learn1_7.png"
+alt="HTML visualization with scikit-learn 1.7"
+style="width:50%"
+/>
+<figcaption>
+HTML visualization with scikit-learn version 1.7
+</figcaption>
+</figure>
+
+
+## Second milestone: Links to parameters documentation and tooltip preview
+
+This feature was further enhanced in version 1.8, released in December 2025.
+We added tooltips that provide documentation for each parameter, 
+as well as links to the online documentation. 
+See the GIF below or this example for more details: 
+[Displaying estimators and complex pipelines](https://scikit-learn.org/
+stable/auto_examples/miscellaneous/plot_estimator_representation.html).
+
+
+<figure>
+<img src="/assets/images/posts_images/enhancing-UX/scikit-learn-1_8.gif"
+alt="HTML visualization with scikit-learn 1.8" />
+<figcaption>
+HTML visualization after scikit-learn 1.8
+</figcaption>
+</figure>
+
+## Planned improvements
+
+More features are now being implemented. In particular, users will be able to 
+visualize feature names and values, display fitted attributes and further improve 
+the overall appearance of the interactive displays.
+
+