回答編集履歴
3
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answer
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@@ -43,8 +43,8 @@
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43
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# モデルを読み込む。
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loaded_model = pickle.load(open(filename, "rb"))
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-
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acc_after_load = loaded_model.score(X, y) # 読み込み後にスコア計算
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# 一致するかどうか
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print(np.isclose(acc_before_save,
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print(np.isclose(acc_before_save, acc_after_load)) # True
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```
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2
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answer
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@@ -8,4 +8,43 @@
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> best_estimator_: Estimator that was chosen by the search
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[sklearn.model_selection.GridSearchCV — scikit-learn 0.21.3 documentation](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.GridSearchCV.html)
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[sklearn.model_selection.GridSearchCV — scikit-learn 0.21.3 documentation](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.GridSearchCV.html)
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## 追記
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```python
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import pickle
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from sklearn import metrics
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from sklearn.datasets import make_blobs
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from sklearn.model_selection import GridSearchCV
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from sklearn.svm import SVC
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# データセットを作成する。
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X, y = make_blobs(n_samples=1000, centers=2, random_state=0)
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# グリッドサーチを行う。
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param_grid = {
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"C": [0.1, 1, 10, 100, 1000],
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"gamma": [1, 0.1, 0.01, 0.001, 0.0001],
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"kernel": ["rbf"],
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}
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clf = GridSearchCV(SVC(), param_grid, refit=True, verbose=0, cv=3)
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clf.fit(X, y)
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filename = "ERP(SVM).sav"
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acc_before_save = clf.score(X, y) # 保存前にスコア計算
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# モデルを保存する。
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pickle.dump(clf.best_estimator_, open(filename, "wb"))
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# モデルを読み込む。
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loaded_model = pickle.load(open(filename, "rb"))
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acc_after_save = loaded_model.score(X, y) # 読み込み後にスコア計算
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# 一致するかどうか
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print(np.isclose(acc_before_save, acc_after_save)) # True
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```
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1
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answer
CHANGED
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File without changes
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