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New_version_sklearn (#56)

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* 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
This commit is contained in:
Ricardo Montañana Gómez
2023-01-15 01:21:32 +01:00
committed by GitHub
parent c37f044e3a
commit 5b791bc5bf
4 changed files with 254 additions and 254 deletions
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36
notebooks/gridsearch.ipynb
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@@ -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}"
]
},
{

2
stree/Strees.py
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@@ -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,

2
stree/_version.py
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@@ -1 +1 @@
__version__ = "1.3.0"
__version__ = "1.3.1"

2
stree/tests/Stree_test.py
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@@ -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",