回答編集履歴
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```
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joblibはどこに・・・
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---
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mkgreiさんに教えて頂いた[リンク](https://stackoverflow.com/questions/40803684/parallel-error-with-gridsearchcv-works-fine-with-other-methods)により質問文のコードを改造した処
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Windows環境でもエラーは発生しないようにできました。
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```Python
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import numpy as np
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from sklearn import datasets
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from sklearn.model_selection import GridSearchCV
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from sklearn.linear_model import LogisticRegression
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from sklearn.decomposition import PCA
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from sklearn.svm import SVC
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from sklearn.pipeline import Pipeline
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from sklearn.model_selection import train_test_split
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from sklearn.model_selection import RandomizedSearchCV
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def main() ->None:
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digits = datasets.load_digits()
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X, y = digits.data, digits.target
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X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=0)
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clf1 = LogisticRegression()
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clf2 = SVC()
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estimators = [('pca', PCA()),
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('clf', clf1)]
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pipe1 = Pipeline(estimators)
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param1 = {'clf__C': [1e-5, 1e-3, 1e-2, 1, 1e2, 1e5, 1e10],
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'pca__whiten': [True, False]}
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gs = GridSearchCV(pipe1, param1)
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gs.fit(X_train, y_train)
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print(gs.score(X_test, y_test))
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estimators = [('pca', PCA()),
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('clf', SVC())]
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pipe2 = Pipeline(estimators)
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gamma_range_exp = np.arange(-10.0, 0.0, 3)
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gamma_range = 10 ** gamma_range_exp
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param2 = {'clf__C': [1e-5, 1e-3, 1e-2, 1, 1e2, 1e5, 1e10],
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'clf__kernel': ['rbf', 'linear'],
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'clf__gamma': gamma_range,
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'pca__whiten': [True, False],
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'pca__n_components': [30, 20, 10]}
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print('start')
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gs = RandomizedSearchCV(pipe2, param2, n_jobs=-1, verbose=2)
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gs.fit(X_train, y_train)
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if __name__ == '__main__':
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main()
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```
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追記
test
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@@ -70,7 +70,7 @@
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OS: Windows 10
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-
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PyCharmより実行。
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```txt
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@@ -59,3 +59,23 @@
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```
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◇実行環境
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python: 3.6.5
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numpy: 1.13.3
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sklearn: 0.19.1
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OS: Windows 10
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```txt
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ImportError: [joblib] Attempting to do parallel computing without protecting your import on a system that does not support forking. To use parallel-computing in a script, you must protect your main loop using "if __name__ == '__main__'". Please see the joblib documentation on Parallel for more information
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```
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joblibはどこに・・・
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2
追記
test
CHANGED
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@@ -37,3 +37,25 @@
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追記
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[VotingClassifierを使いつつGridSearchCV/RandomizedSearchCVでパラメータチューニング](https://qiita.com/yagays/items/a503117bd06bb938fdb9)
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---
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```Python
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param2 ={'clf__C':[1e-5, 1e-3, 1e-2, 1, 1e2, 1e5, 1e10],
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'clf__kernel':['rbf', 'linear'],
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'clf__gamma': gamma_range,
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'pca__whiten':[True,False],
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'pca__n_components': [30, 20, 10]}
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```
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追記
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@@ -33,3 +33,7 @@
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```
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追記
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[VotingClassifierを使いつつGridSearchCV/RandomizedSearchCVでパラメータチューニング](https://qiita.com/yagays/items/a503117bd06bb938fdb9)
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