v0.6.11 RC2

Author: paulbkoch

.github/workflows/ci.yml

@@ -227,19 +227,27 @@ jobs:
           python -m pip install "bld/sdist/$install_file.tar.gz[debug,notebook,plotly,lime,sensitivity,shap,linear,treeinterpreter,aplr,dash,skoperules,excel,testing]"
           cd "docs/"
           pip install -r requirements.txt
-          /bin/sh ./build.sh
+          if ! /bin/sh ./build.sh; then
+            echo "::warning title=docs build::Building of docs failed"
+            exit 78  # no longer works in github, but would mark action step with a warning
+          fi
       - name: Mark step with a warning
         if: ${{ steps.build_docs.outcome == 'failure' }}
         uses: actions/github-script@v6
         with:
           script: |
-            github.rest.checks.create({
+            await github.rest.checks.create({
               owner: context.repo.owner,
               repo: context.repo.repo,
               name: 'Failed building docs',
               head_sha: context.sha,
               status: 'completed',
-              conclusion: 'neutral'
+              conclusion: 'neutral',
+              completed_at: new Date().toISOString(),
+              output: {
+                title: 'Failed building docs',
+                summary: 'Failed building docs.'
+              }
             })
       - name: Publish docs
         uses: actions/upload-artifact@v4

README.md

@@ -712,6 +712,7 @@ We also build on top of many great packages. Please check them out!
 - [Explainable Artificial Intelligence in Job Recommendation Systems](http://essay.utwente.nl/96974/1/Tran_MA_EEMCS.pdf)
 - [Diagnosis uncertain models for medical risk prediction](https://arxiv.org/pdf/2306.17337.pdf)
 - [Extending Explainable Boosting Machines to Scientific Image Data](https://arxiv.org/pdf/2305.16526.pdf)
+- [Exploring explanation deficits in subclinical mastitis detection with explainable boosting machines](https://link.springer.com/article/10.1007/s44279-025-00246-z)
 - [Pest Presence Prediction Using Interpretable Machine Learning](https://arxiv.org/pdf/2205.07723.pdf)
 - [Key Thresholds and Relative Contributions of Knee Geometry, Anteroposterior Laxity, and Body Weight as Risk Factors for Noncontact ACL Injury](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10184233/pdf/10.1177_23259671231163627.pdf)
 - [A clinical prediction model for 10-year risk of self-reported osteoporosis diagnosis in pre- and perimenopausal women](https://pubmed.ncbi.nlm.nih.gov/37273115/)

python/interpret-core/interpret/_version.py

@@ -2,4 +2,4 @@
 # Distributed under the MIT software license
 
 # NOTE: Version is replaced by a regex script.
-__version__ = "0.6.10"
+__version__ = "0.6.11"

python/interpret-core/setup.py

@@ -12,7 +12,7 @@
 from setuptools.command.sdist import sdist
 
 # NOTE: Version is replaced by a regex script.
-version = "0.6.10"
+version = "0.6.11"
 
 
 def _copy_native_code_to_setup():

python/interpret/setup.py

@@ -5,7 +5,7 @@
 
 name = "interpret"
 # NOTE: Version is replaced by a regex script.
-version = "0.6.10"
+version = "0.6.11"
 long_description = """
 In the beginning machines learned in darkness, and data scientists struggled in the void to explain them.
 

shared/vis/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@interpretml/interpret-inline",
-  "version": "0.6.10",
+  "version": "0.6.11",
   "description": "Interpret inline library for rendering visualizations across all notebook environments.",
   "main": "index.js",
   "keywords": [],