Add wodt clf

Add execution results of RaF, RoF and RRoF
Fix fit time in database records

experimentation/Database.py

@@ -345,8 +345,8 @@ class Outcomes(BD):
                 float(results["test_score"].std()),
             ],
             [
-                float(results["score_time"].mean()),
-                float(results["score_time"].std()),
+                float(results["fit_time"].mean()),
+                float(results["fit_time"].std()),
             ],
             parameters,
         )
@@ -441,8 +441,8 @@ class Hyperparameters(BD):
             float(outcomes["test_score_std"]),
         ]
         time_spent = [
-            float(outcomes["score_time"]),
-            float(outcomes["score_time_std"]),
+            float(outcomes["fit_time"]),
+            float(outcomes["fit_time_std"]),
         ]
         self.mirror(
             grid_type,

experimentation/Models.py

@@ -11,6 +11,7 @@ from sklearn.svm import LinearSVC  # type: ignore
 from sklearn.tree import DecisionTreeClassifier  # type: ignore
 from odte import Odte
 from sklearn_oblique_tree.oblique import ObliqueTree
+from wodt import TreeClassifier
 
 
 class ModelBase(ABC):
@@ -95,6 +96,31 @@ class ModelOc1(ModelBase):
             self._param_grid = [self._rbf]
 
 
+class ModelWodt(ModelBase):
+    def __init__(self, random_state: Optional[int] = None) -> None:
+        self._clf = TreeClassifier()
+        super().__init__(random_state)
+        self._model_name = "wodt"
+        self._linear = {
+            "random_state": [self._random_state],
+        }
+        self._rbf = {}
+        self._poly = {}
+        self._param_grid = [
+            self._linear,
+            self._poly,
+            self._rbf,
+        ]
+
+    def select_params(self, kernel: str) -> None:
+        if kernel == "linear":
+            self._param_grid = [self._linear]
+        elif kernel == "poly":
+            self._param_grid = [self._poly]
+        else:
+            self._param_grid = [self._rbf]
+
+
 class ModelStree(ModelBase):
     def __init__(self, random_state: Optional[int] = None) -> None:
         self._clf = Stree()