New_version_sklearn (#56)

* test: 🧪 Update max_iter as int in test_multiclass_dataset

* refactor: 📝 Rename base_estimator to estimator as the former is deprectated in notebook

* refactor: 📌 Convert max_iter to int as needed in sklearn 1.2

* chore: 🔖 Update version info to 1.3.1

notebooks/gridsearch.ipynb

@@ -133,33 +133,33 @@
         "    'base_estimator': [Stree(random_state=random_state)],\n",
         "    'n_estimators': [10, 25],\n",
         "    'learning_rate': [.5, 1],\n",
-    "    'base_estimator__split_criteria': ['max_samples', 'impurity'],\n",
-    "    'base_estimator__tol': [.1,  1e-02],\n",
-    "    'base_estimator__max_depth': [3, 5, 7],\n",
-    "    'base_estimator__C': [1, 7, 55],\n",
-    "    'base_estimator__kernel': ['linear']\n",
+        "    'estimator__split_criteria': ['max_samples', 'impurity'],\n",
+        "    'estimator__tol': [.1,  1e-02],\n",
+        "    'estimator__max_depth': [3, 5, 7],\n",
+        "    'estimator__C': [1, 7, 55],\n",
+        "    'estimator__kernel': ['linear']\n",
         "},\n",
         "{\n",
         "    'base_estimator': [Stree(random_state=random_state)],\n",
         "    'n_estimators': [10, 25],\n",
         "    'learning_rate': [.5, 1],\n",
-    "    'base_estimator__split_criteria': ['max_samples', 'impurity'],\n",
-    "    'base_estimator__tol': [.1,  1e-02],\n",
-    "    'base_estimator__max_depth': [3, 5, 7],\n",
-    "    'base_estimator__C': [1, 7, 55],\n",
-    "    'base_estimator__degree': [3, 5, 7],\n",
-    "    'base_estimator__kernel': ['poly']\n",
+        "    'estimator__split_criteria': ['max_samples', 'impurity'],\n",
+        "    'estimator__tol': [.1,  1e-02],\n",
+        "    'estimator__max_depth': [3, 5, 7],\n",
+        "    'estimator__C': [1, 7, 55],\n",
+        "    'estimator__degree': [3, 5, 7],\n",
+        "    'estimator__kernel': ['poly']\n",
         "},\n",
         "{\n",
         "    'base_estimator': [Stree(random_state=random_state)],\n",
         "    'n_estimators': [10, 25],\n",
         "    'learning_rate': [.5, 1],\n",
-    "    'base_estimator__split_criteria': ['max_samples', 'impurity'],\n",
-    "    'base_estimator__tol': [.1,  1e-02],\n",
-    "    'base_estimator__max_depth': [3, 5, 7],\n",
-    "    'base_estimator__C': [1, 7, 55],\n",
-    "    'base_estimator__gamma': [.1, 1, 10],\n",
-    "    'base_estimator__kernel': ['rbf']\n",
+        "    'estimator__split_criteria': ['max_samples', 'impurity'],\n",
+        "    'estimator__tol': [.1,  1e-02],\n",
+        "    'estimator__max_depth': [3, 5, 7],\n",
+        "    'estimator__C': [1, 7, 55],\n",
+        "    'estimator__gamma': [.1, 1, 10],\n",
+        "    'estimator__kernel': ['rbf']\n",
         "}]"
       ]
     },
@@ -214,7 +214,7 @@
         "                   base_estimator=Stree(C=55, max_depth=7, random_state=1,\n",
         "                                        split_criteria='max_samples', tol=0.1),\n",
         "                   learning_rate=0.5, n_estimators=25, random_state=1)\n",
-    "Best hyperparameters:  {'base_estimator': Stree(C=55, max_depth=7, random_state=1, split_criteria='max_samples', tol=0.1), 'base_estimator__C': 55, 'base_estimator__kernel': 'linear', 'base_estimator__max_depth': 7, 'base_estimator__split_criteria': 'max_samples', 'base_estimator__tol': 0.1, 'learning_rate': 0.5, 'n_estimators': 25}"
+        "Best hyperparameters:  {'base_estimator': Stree(C=55, max_depth=7, random_state=1, split_criteria='max_samples', tol=0.1), 'estimator__C': 55, 'estimator__kernel': 'linear', 'estimator__max_depth': 7, 'estimator__split_criteria': 'max_samples', 'estimator__tol': 0.1, 'learning_rate': 0.5, 'n_estimators': 25}"
       ]
     },
     {

stree/Strees.py

@@ -139,7 +139,7 @@ class Stree(BaseEstimator, ClassifierMixin):
         self,
         C: float = 1.0,
         kernel: str = "linear",
-        max_iter: int = 1e5,
+        max_iter: int = int(1e5),
         random_state: int = None,
         max_depth: int = None,
         tol: float = 1e-4,

stree/_version.py

@@ -1 +1 @@
-__version__ = "1.3.0"
+__version__ = "1.3.1"

stree/tests/Stree_test.py

@@ -306,7 +306,7 @@ class Stree_test(unittest.TestCase):
             for criteria in ["max_samples", "impurity"]:
                 for kernel in self._kernels:
                     clf = Stree(
-                        max_iter=1e4,
+                        max_iter=int(1e4),
                         multiclass_strategy="ovr"
                         if kernel == "liblinear"
                         else "ovo",