update exampls in doc

softmin · Aug 22, 2024 · bf71128 · bf71128
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diff --git a/.ipynb_checkpoints/SVM-checkpoint.ipynb b/.ipynb_checkpoints/SVM-checkpoint.ipynb
diff --git a/doc/source/example.rst b/doc/source/example.rst
@@ -8,16 +8,16 @@ Example Gallery
    :caption: A few links
    :name: rst-link-gallery
 
-   examples/ReHLine_QR
-   examples/ReHLine_SVM_FairSVM
+   examples/QR.ipynb
+   examples/SVM.ipynb
+   examples/FairSVM.ipynb
 
 List of Examples
 ----------------
 
 .. toctree::
-   :maxdepth: 0
-
-   examples/ReHLine_QR.ipynb
-   examples/ReHLine_SVM_FairSVM.ipynb
-
+   :maxdepth: 1
 
+   examples/QR.ipynb
+   examples/SVM.ipynb
+   examples/FairSVM.ipynb
diff --git a/doc/source/examples/.ipynb_checkpoints/FairSVM-checkpoint.ipynb b/doc/source/examples/.ipynb_checkpoints/FairSVM-checkpoint.ipynb
diff --git a/doc/source/examples/FairSVM.ipynb b/doc/source/examples/FairSVM.ipynb
@@ -31,6 +31,7 @@
     "* $\\mathbf{\\rho} \\in \\mathbb{R}_+^{d_0}$ is a vector of constants that trade-off predictive accuracy and fairness\n",
     "\n",
     "The constraints limit the correlation between the sensitive features and the decision function, ensuring fairness in the predictions.\n",
+    "\n",
     "> **Note.** Since the hinge loss is a plq function, and fairness constraints are linear, thus we can solve it by `rehline.plqERM_Ridge`."
    ]
   },

diff --git a/doc/source/examples/SVM.ipynb b/doc/source/examples/SVM.ipynb
diff --git a/doc/source/index.rst b/doc/source/index.rst
@@ -36,9 +36,6 @@
 - Paper: `NeurIPS | 2023 <https://openreview.net/pdf?id=3pEBW2UPAD>`_
 .. - Open Source: `MIT license <https://opensource.org/licenses/MIT>`_
 
-`ReHLine` is designed to be a computationally efficient 
-and practically useful software package for large-scale regularized ERMs.
-
 The proposed **ReHLine** solver has appealing exhibits appealing properties:
 
 .. list-table::
@@ -78,6 +75,5 @@ If you use this code please star 🌟 the repository and cite the following pape
    :maxdepth: 2
    :hidden:
 
-   tutorials
    example
    benchmark
diff --git a/rehline/__init__.py b/rehline/__init__.py
@@ -1,5 +1,6 @@
 # Import from internal C++ module
-from ._base import ReHLine_solver, _BaseReHLine, _make_loss_rehline_param
+from ._base import (ReHLine_solver, _BaseReHLine,
+                    _make_constraint_rehline_param, _make_loss_rehline_param)
 from ._class import ReHLine, plqERM_Ridge
 from ._data import make_fair_classification
 from ._internal import rehline_internal, rehline_result
-Original file line number
+Diff line change
@@ Expand Up / @@ -31,6 +31,7 @@ @@
         "* $\\mathbf{\\rho} \\in \\mathbb{R}_+^{d_0}$ is a vector of constants that trade-off predictive accuracy and fairness\n",
         "\n",
         "The constraints limit the correlation between the sensitive features and the decision function, ensuring fairness in the predictions.\n",
+        "\n",
         "> **Note.** Since the hinge loss is a plq function, and fairness constraints are linear, thus we can solve it by `rehline.plqERM_Ridge`."
        ]
       },
@@ Expand Down @@