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  1. 検索関連の設定

    fragments = 2 ハイライト生成方法 OpenSearchのハイライトの生成方法を指定します。...
    fess.codelibs.org/ja/14.19/config/search-config.html
    Fri Apr 18 02:35:52 UTC 2025
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  2. 検索API

    "2" , "3" , "4" , "5" ], "partial"...
    fess.codelibs.org/ja/14.19/api/api-search.html
    Fri Apr 18 02:35:53 UTC 2025
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  3. 3.1. Cross-validation: evaluating estimator per...

    2 , 2 , 2 , 2 ] >>> groups = [ 1 , 1 , 2 , 2 , 3 , 3...)) [2 3] [0 1] [1 3] [0 2] [1 2] [0 3] [0 3] [1 2] [0 2] [1 3]...
    scikit-learn.org/stable/modules/cross_validation.html
    Sat Apr 19 00:31:21 UTC 2025
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  4. RepeatedKFold — scikit-learn 1.6.1 documentation

    2 ], [ 3 , 4 ], [ 1 , 2 ], [ 3 , 4 ]]) >>>...RepeatedKFold ( n_splits = 2 , n_repeats = 2 , random_state = 2652124...
    scikit-learn.org/stable/modules/generated/sklearn.model_selection.RepeatedKFold.html
    Sat Apr 19 00:31:21 UTC 2025
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  5. 1.1. Linear Models — scikit-learn 1.6.1 documen...

    x_1 + w_2 x_2 + w_3 x_1 x_2 + w_4 x_1^2 + w_5 x_2^2\] The (sometimes...\([x_1, x_2]\) to \([1, x_1, x_2, x_1^2, x_1 x_2, x_2^2]\) , and...
    scikit-learn.org/stable/modules/linear_model.html
    Sat Apr 19 00:31:22 UTC 2025
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  6. r2_score — scikit-learn 1.6.1 documentation

    y_true = [ - 2 , - 2 , - 2 ] >>> y_pred = [ - 2 , - 2 , - 2 ] >>> r2_score...y_true = [ - 2 , - 2 , - 2 ] >>> y_pred = [ - 2 , - 2 , - 2 + 1e-8...
    scikit-learn.org/stable/modules/generated/sklearn.metrics.r2_score.html
    Sat Apr 19 00:31:21 UTC 2025
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  7. cross_validation.rst.txt

    2, 2, 2, 2] >>> groups = [1, 1, 2, 2, 3, 3, 3] >>>...test)) [2 3] [0 1] [1 3] [0 2] [1 2] [0 3] [0 3] [1 2] [0 2] [1 3]...
    scikit-learn.org/stable/_sources/modules/cross_validation.rst.txt
    Sat Apr 19 00:31:21 UTC 2025
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  8. linear_model.rst.txt

    x_1 + w_2 x_2 + w_3 x_1 x_2 + w_4 x_1^2 + w_5 x_2^2 The (sometimes...:math:`[x_1, x_2]` to :math:`[1, x_1, x_2, x_1^2, x_1 x_2, x_2^2]`, and...
    scikit-learn.org/stable/_sources/modules/linear_model.rst.txt
    Sat Apr 19 00:31:21 UTC 2025
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  9. model_evaluation.rst.txt

    labeling1 = [2, 0, 2, 2, 0, 1] >>> labeling2 = [0, 0, 2, 2, 0, 2] >>>...y_true = [2, 0, 2, 2, 0, 1] >>> y_pred = [0, 0, 2, 2, 0, 2] >>> ...
    scikit-learn.org/stable/_sources/modules/model_evaluation.rst.txt
    Sat Apr 19 00:31:22 UTC 2025
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  10. RegressorMixin — scikit-learn 1.6.1 documentation

    2 ], [ 2 , 3 ], [ 3 , 4 ]]) >>> y =...float \(R^2\) of self.predict(X) w.r.t. y . Notes The \(R^2\) score...
    scikit-learn.org/stable/modules/generated/sklearn.base.RegressorMixin.html
    Sat Apr 19 00:31:20 UTC 2025
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