feat: Add support for CFVAE

experiments/experimental_setup.yaml

@@ -138,5 +138,9 @@ recourse_methods:
     hyperparams:
       loss_type: "BCE"
       binary_cat_features: True
+  cfvae:
+    hyperparams:
+       encoded_size: 10
+       train: True
   roar:
     hyperparams:

experiments/results.csv

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+cfvae,boston_housing,linear,13.0,2.68523783144457,1.3536098527317284,1.0,0.0,8.0,,,
+cfvae,boston_housing,linear,12.0,2.6634623119522995,0.9450720482092089,0.5413446724414825,0.0,7.0,,,
+cfvae,boston_housing,linear,12.0,2.7303082781093764,0.9808185383635877,0.541551798582077,0.0,7.0,,,
+cfvae,boston_housing,linear,13.0,2.1282869963624558,1.1681508890811234,1.0,0.0,7.0,,,
+cfvae,boston_housing,linear,11.0,1.1642179021592083,0.2220489567468797,0.3127339951535488,0.0,7.0,,,
+cfvae,boston_housing,linear,12.0,1.0237826877700886,0.15038662312775705,0.24312054669597183,0.0,10.0,,,
+cfvae,boston_housing,linear,13.0,2.354798590209251,1.2301028537404475,1.0,0.0,11.0,,,
+cfvae,boston_housing,linear,12.0,2.148736169232081,1.2422881142210536,1.0,0.0,1.0,,,
 roar,adult,linear,5.0,9.618374680646278,18.55040773192179,2.03277587890625,1.0,5.0,0.05999999999999994,1.0,1.0735000799999999
 roar,adult,linear,5.0,8.90917690170632,15.907446315902012,1.8774079084396362,1.0,5.0,,,
 roar,adult,linear,5.0,14.060748848458747,39.60930977247996,2.9490909576416016,1.0,5.0,,,

experiments/run_experiment.py

@@ -164,7 +164,9 @@ def initialize_recourse_method(
         return Revise(mlmodel, data, hyperparams)
     elif "wachter" in method:
         return Wachter(mlmodel, hyperparams)
-    elif method == "roar":
+    elif "cfvae" in method:
+        return CFVAE(mlmodel, hyperparams)
+    elif "roar" in method:
         return Roar(mlmodel, hyperparams)
     else:
         raise ValueError("Recourse method not known")
@@ -195,7 +197,7 @@ def create_parser():
     -r, --recourse_method: Specifies recourse methods for the experiment.
         Default: ["dice", "cchvae", "cem", "cem_vae", "clue", "cruds", "face_knn", "face_epsilon", "gs", "mace", "revise", "wachter"].
         Choices: ["dice", "ar", "causal_recourse", "cchvae", "cem", "cem_vae", "claproar", "clue", "cruds", "face_knn", "face_epsilon", "feature_tweak",
-            "focus", "gravitational", "greedy", "gs", "mace", "revise", "wachter", "roar"].
+            "focus", "gravitational", "greedy", "gs", "mace", "revise", "wachter", "cfvae", "roar"].
     -n, --number_of_samples: Specifies the number of instances per dataset.
         Default: 20.
     -s, --train_split: Specifies the split of the available data used for training.
@@ -262,6 +264,7 @@ def create_parser():
             "gs",
             "revise",
             "wachter",
+            "cfvae",
             "roar",
         ],
         choices=[
@@ -284,6 +287,7 @@ def create_parser():
             "mace",
             "revise",
             "wachter",
+            "cfvae",
             "roar",
         ],
         help="Recourse methods for experiment",
@@ -364,6 +368,7 @@ def create_parser():
         "gravitational",
         "wachter",
         "revise",
+        "cfvae",
         "roar",
     ]
     sklearn_methods = ["feature_tweak", "focus", "mace"]

methods/__init__.py

@@ -4,6 +4,7 @@
 from .catalog import (
     CCHVAE,
     CEM,
+    CFVAE,
     CRUD,
     FOCUS,
     MACE,

methods/catalog/__init__.py

@@ -3,6 +3,7 @@
 from .causal_recourse import CausalRecourse
 from .cchvae import CCHVAE
 from .cem import CEM
+from .cfvae import CFVAE
 from .claproar import ClaPROAR
 from .clue import Clue
 from .crud import CRUD

methods/catalog/cfvae/__init__.py

@@ -0,0 +1,3 @@
+# flake8: noqa
+
+from .model import CFVAE