Merge branch 'develop' of github.com:holistic-ai/holisticai into feat…

…ure/dataset_shift/#221
holistic-ai · Oct 31, 2024 · 09fab56 · 09fab56
2 parents 2586a4a + 1c5293e
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diff --git a/.github/workflows/feature-workflow.yml b/.github/workflows/feature-workflow.yml
@@ -16,10 +16,10 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4.1.7
+        uses: actions/checkout@v4.2.2
 
       - name: Set up Python
-        uses: actions/setup-python@v5.2.0
+        uses: actions/setup-python@v5.3.0
         with:
           python-version: "3.9"
           cache: "pip"

diff --git a/.github/workflows/publish-workflow.yml b/.github/workflows/publish-workflow.yml
@@ -14,15 +14,15 @@ jobs:
           private-key: ${{ secrets.APPLICATION_PRIVATE_KEY }}
 
       - name: Checkout code
-        uses: actions/checkout@v4.1.7
+        uses: actions/checkout@v4.2.2
         with:
           fetch-tags: true
           fetch-depth: 0
           ref: main
           token: ${{ steps.app-token.outputs.token }} # Needed to trigger other actions
 
       - name: Set up Python
-        uses: actions/setup-python@v5.2.0
+        uses: actions/setup-python@v5.3.0
         with:
             python-version: "3.9"
 

diff --git a/.github/workflows/release-workflow.yml b/.github/workflows/release-workflow.yml
@@ -20,15 +20,15 @@ jobs:
           private-key: ${{ secrets.APPLICATION_PRIVATE_KEY }}
 
       - name: Checkout code
-        uses: actions/checkout@v4.1.7
+        uses: actions/checkout@v4.2.2
         with:
           fetch-tags: true
           fetch-depth: 0
           ref: main
           token: ${{ steps.app-token.outputs.token }} # Needed to trigger other actions
 
       - name: Set up Python
-        uses: actions/setup-python@v5.2.0
+        uses: actions/setup-python@v5.3.0
         with:
           python-version: "3.9"
 

diff --git a/docs/source/conf.py b/docs/source/conf.py
@@ -67,13 +67,7 @@
     "sphinxcontrib.youtube",
 ]
 
-intersphinx_mapping = {
-    "python3": ("https://docs.python.org/3", None),
-    "numpy": ("https://numpy.org/doc/stable/", None),
-    "pandas": ("https://pandas.pydata.org/pandas-docs/stable/", None),
-    "sklearn": ("https://scikit-learn.org/stable/", None),
-    "matplotlib": ("https://matplotlib.org/stable/", None)
-}
+
 
 source_suffix = {
     '.rst': 'restructuredtext',
@@ -82,7 +76,7 @@
 
 
 nbsphinx_allow_errors = True  # Permitir errores en los notebooks
-nbsphinx_execute = 'auto'  # Puede ser 'auto', 'always', o 'never'
+nbsphinx_execute = 'never'  # Puede ser 'auto', 'always', o 'never'
 
 html_show_sourcelink = False
 # autodoc options

diff --git a/docs/source/gallery/index.rst b/docs/source/gallery/index.rst
@@ -14,3 +14,5 @@ This gallery contains a collection of examples that demonstrate the usage of ``h
     Explainability <tutorials/explainability>
 
     Robustness <tutorials/robustness>
+
+    Security <tutorials/security>
diff --git a/docs/source/gallery/tutorials/explainability.rst b/docs/source/gallery/tutorials/explainability.rst
@@ -19,6 +19,11 @@ Here are some tutorials where different systems are assessed using the metrics.
    - `Measuring XAI using SHAP Feature Importance <explainability/demos/local_shap.ipynb>`_
    - `Measuring XAI using LIME Feature Importance <explainability/demos/local_lime.ipynb>`_
    - `Measuring XAI using Tree Based Metrics <explainability/demos/tree_based_metrics.ipynb>`_
+   - `Measuring XAI using Global Feature Importance <explainability/demos/xai_metrics_global_feature_importance.ipynb>`_
+   - `Measuring XAI using Local Feature Importance <explainability/demos/xai_metrics_local_feature_importance.ipynb>`_
+   - `Measuring XAI using Surrogate <explainability/demos/xai_metrics_surrogate.ipynb>`_
 
 - Examples
-   - `Explainability in Machine Learning - Clinical Records Analysis <explainability/examples/example_clinical_records.ipynb>`_
+   - `Explainability in Machine Learning - Clinical Records Analysis <explainability/examples/example_clinical_records.ipynb>`_
+   - `Explainability in Machine Learning - US Crime <explainability/examples/measuring_explainability_us_crime.ipynb>`_
+   - `Explainability in Machine Learning - Adult Dataset <explainability/examples/meauring_explainability_adult.ipynb>`_
diff --git a/docs/source/gallery/tutorials/explainability/demos/entropy_measures.ipynb b/docs/source/gallery/tutorials/explainability/demos/entropy_measures.ipynb
@@ -33,7 +33,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [
     {
@@ -101,7 +101,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "testing",
    "language": "python",
    "name": "python3"
   },

diff --git a/docs/source/gallery/tutorials/explainability/demos/global_permutation.ipynb b/docs/source/gallery/tutorials/explainability/demos/global_permutation.ipynb
diff --git a/docs/source/gallery/tutorials/explainability/demos/global_surrogate.ipynb b/docs/source/gallery/tutorials/explainability/demos/global_surrogate.ipynb
@@ -113,7 +113,7 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Rank Alignment</th>\n",
-       "      <td>0.250000</td>\n",
+       "      <td>0.083333</td>\n",
        "      <td>1.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
@@ -123,8 +123,8 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Spread Divergence</th>\n",
-       "      <td>0.060155</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>0.939845</td>\n",
+       "      <td>1.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Surrogate Accuracy Score</th>\n",
@@ -141,9 +141,9 @@
        "Alpha Importance Score    0.009901        0.0\n",
        "XAI Ease Score            1.000000        1.0\n",
        "Position Parity           0.250000        1.0\n",
-       "Rank Alignment            0.250000        1.0\n",
+       "Rank Alignment            0.083333        1.0\n",
        "Spread Ratio              0.147387        0.0\n",
-       "Spread Divergence         0.060155        0.0\n",
+       "Spread Divergence         0.939845        1.0\n",
        "Surrogate Accuracy Score  0.007099        1.0"
       ]
      },
@@ -221,7 +221,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 13,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2024-09-08T06:17:41.257635Z",
@@ -237,7 +237,7 @@
        "0.7957987838584853"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -260,7 +260,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 14,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2024-09-08T06:17:41.520942Z",
@@ -328,8 +328,8 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Spread Divergence</th>\n",
-       "      <td>0.043963</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>0.956037</td>\n",
+       "      <td>1.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Surrogate Accuracy Score</th>\n",
@@ -348,11 +348,11 @@
        "Position Parity           0.000000        1.0\n",
        "Rank Alignment            0.000000        1.0\n",
        "Spread Ratio              0.135284        0.0\n",
-       "Spread Divergence         0.043963        0.0\n",
+       "Spread Divergence         0.956037        1.0\n",
        "Surrogate Accuracy Score  0.980873        1.0"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -380,7 +380,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 15,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2024-09-08T06:17:42.755085Z",
@@ -396,7 +396,7 @@
        "<Axes: >"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -426,7 +426,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 16,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2024-09-08T06:17:43.140051Z",
@@ -442,7 +442,7 @@
        "0.810126582278481"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -465,7 +465,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 17,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2024-09-08T06:17:43.190705Z",
@@ -523,7 +523,7 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Rank Alignment</th>\n",
-       "      <td>0.074074</td>\n",
+       "      <td>0.150000</td>\n",
        "      <td>1.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
@@ -533,8 +533,8 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Spread Divergence</th>\n",
-       "      <td>0.195874</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>0.804126</td>\n",
+       "      <td>1.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Surrogate Accuracy Score</th>\n",
@@ -551,13 +551,13 @@
        "Alpha Importance Score    0.115385        0.0\n",
        "XAI Ease Score            0.888889        1.0\n",
        "Position Parity           0.000000        1.0\n",
-       "Rank Alignment            0.074074        1.0\n",
+       "Rank Alignment            0.150000        1.0\n",
        "Spread Ratio              0.437464        0.0\n",
-       "Spread Divergence         0.195874        0.0\n",
+       "Spread Divergence         0.804126        1.0\n",
        "Surrogate Accuracy Score  0.848101        1.0"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 17,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -585,7 +585,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 18,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2024-09-08T06:17:43.901406Z",
@@ -601,7 +601,7 @@
        "<Axes: >"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 18,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -625,7 +625,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "testing",
    "language": "python",
    "name": "python3"
   },