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  1. BaseEstimator — scikit-learn 1.8.0 docume...

    {'param': 2} >>> X = np . array ([[ 1 , 2 ], [ 2 , 3 ],...y ) . predict ( X ) array([2, 2, 2]) >>> estimator ....
    scikit-learn.org/stable/modules/generated/sklearn.base.BaseEstimator.html
    Mon Jan 26 11:09:12 GMT 2026
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  2. mean_poisson_deviance — scikit-learn 1.8....

    = [ 2 , 0 , 1 , 4 ] >>> y_pred = [ 0.5 , 0.5 , 2. , 2....2. ] >>> mean_poisson_deviance ( y_true , y_pred ) 1.4260......
    scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_poisson_deviance.html
    Mon Feb 02 09:23:44 GMT 2026
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  3. Archiv

    herunterladen Methode 2: Repository mit Git klonen Schritt 2: Überprüfung...Installation von OpenSearch Schritt 2: Installation von Fess Schritt...
    fess.codelibs.org/de/archives.html
    Mon Feb 02 02:45:38 GMT 2026
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  4. Plot the decision surface of decision trees tra...

    2 ], [ 0 , 3 ], [ 1 , 2 ], [ 1 , 3 ], [ 2 , 3 ]]): #...boundary ax = plt . subplot ( 2 , 3 , pairidx + 1 ) plt . tight_layout...
    scikit-learn.org/stable/auto_examples/tree/plot_iris_dtc.html
    Mon Feb 02 09:23:44 GMT 2026
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  5. explained_variance_score — scikit-learn 1...

    = [ - 2 , - 2 , - 2 ] >>> y_pred = [ - 2 , - 2 , - 2...= [ - 2 , - 2 , - 2 ] >>> y_pred = [ - 2 , - 2 , - 2...
    scikit-learn.org/stable/modules/generated/sklearn.metrics.explained_variance_score.html
    Mon Jan 26 11:09:12 GMT 2026
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  6. IsotonicRegression — scikit-learn 1.8.0 d...

    float \(R^2\) of self.predict(X) w.r.t. y . Notes The \(R^2\) score...Operations Research Vol. 14, No. 2 (May, 1989), pp. 303-308 Isotone...
    scikit-learn.org/stable/modules/generated/sklearn.isotonic.IsotonicRegression.html
    Mon Jan 26 14:16:29 GMT 2026
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  7. QuadraticDiscriminantAnalysis — scikit-le...

    [ - 2 , - 1 ], [ - 3 , - 2 ], [ 1 , 1 ], [ 2 , 1 ], [ 3...3 , 2 ]]) >>> y = np . array ([ 1 , 1 , 1 , 2 , 2 , 2...
    scikit-learn.org/stable/modules/generated/sklearn.discriminant_analysis.QuadraticDiscriminantAnal...
    Mon Feb 02 09:23:44 GMT 2026
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  8. plot_classifier_comparison.rst.txt

    make_classification( n_features=2, n_redundant=0, n_informative=2, random_state=1,...rng = np.random.RandomState(2) X += 2 * rng.uniform(size=X.shape)...
    scikit-learn.org/stable/_sources/auto_examples/classification/plot_classifier_comparison.rst.txt
    Mon Jan 12 10:07:41 GMT 2026
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  9. plot_multi_metric_evaluation.zip

    range(2, 403, 20)}, scoring=scoring, refit="AUC", n_jobs=2, re...ax.plot( [ X_axis[best_index], ] * 2, [0, best_score], linestyle="-.",...
    scikit-learn.org/stable/_downloads/535778bfbc9b4881da3e662bc2ea8484/plot_multi_metric_evaluation.zip
    Mon Jan 26 11:09:12 GMT 2026
      8.8K bytes
     
  10. QuantileRegressor — scikit-learn 1.8.0 do...

    float \(R^2\) of self.predict(X) w.r.t. y . Notes The \(R^2\) score...n_samples , n_features = 10 , 2 >>> rng = np . random...
    scikit-learn.org/stable/modules/generated/sklearn.linear_model.QuantileRegressor.html
    Mon Jan 26 14:16:30 GMT 2026
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