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  1. Early stopping in Gradient Boosting — scikit-le...

    params = dict ( n_estimators = 1000 , max_depth = 5 , learning_rate...learning_rate = 0.1 , random_state = 42 ) gbm_full = GradientBoostingRegr...
    scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_early_stopping.html
    Wed Jul 02 18:21:48 UTC 2025
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  2. Plotting Cross-Validated Predictions — scikit-l...

    y = load_diabetes ( return_X_y = True ) lr = LinearRegression...y_pred = cross_val_predict ( lr , X , y , cv = 10 ) Since cv=10 ,...
    scikit-learn.org/stable/auto_examples/model_selection/plot_cv_predict.html
    Wed Jul 02 18:21:48 UTC 2025
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  3. r2_score — scikit-learn 1.7.0 documentation

    sample_weight = None , multioutput = 'uniform_average' ,...r2_score >>> y_true = [ 3 , - 0.5 , 2 , 7 ] >>> y_pred = [ 2.5 , 0.0...
    scikit-learn.org/stable/modules/generated/sklearn.metrics.r2_score.html
    Wed Jul 02 18:21:48 UTC 2025
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  4. ShrunkCovariance — scikit-learn 1.7.0 documenta...

    store_precision = True , assume_centered = False , shrinkage = 0.1 ) [source]...multivariate_normal ( mean = [ 0 , 0 ], ... cov = real_cov , ... size = 500 ) >>>...
    scikit-learn.org/stable/modules/generated/sklearn.covariance.ShrunkCovariance.html
    Wed Jul 02 18:21:48 UTC 2025
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  5. 3.4. Metrics and scoring: quantifying the quali...

    y = datasets . load_iris ( return_X_y = True ) >>> clf = svm...greater_is_better = False ) >>> X = [[ 1 ], [ 1 ]] >>> y = [ 0 , 1 ]...
    scikit-learn.org/stable/modules/model_evaluation.html
    Wed Jul 02 18:21:48 UTC 2025
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  6. OutputCodeClassifier — scikit-learn 1.7.0 docum...

    code_size = 1.5 , random_state = None , n_jobs = None ) [source]..., y = make_classification ( n_samples = 100 , n_features = 4 ,...
    scikit-learn.org/stable/modules/generated/sklearn.multiclass.OutputCodeClassifier.html
    Wed Jul 02 18:21:48 UTC 2025
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  7. plot_release_highlights_1_7_0.ipynb

    cv=5, return_estimator=True, return_indices=True)\n_ = Roc...uting=True)\n\nX, y = make_classification(random_state=0)\nX_train,...
    scikit-learn.org/stable/_downloads/b7d178d09f44d400894015228deb0ddb/plot_release_highlights_1_7_0...
    Wed Jul 02 18:21:48 UTC 2025
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  8. GaussianProcessRegressor — scikit-learn 1.7.0 d...

    ( kernel = None , * , alpha = 1e-10 , optimizer = 'fmin_l_bfgs_b'...n_restarts_optimizer = 0 , normalize_y = False , copy_X_train = True , n_targets...
    scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.GaussianProcessRegressor.html
    Wed Jul 02 18:21:48 UTC 2025
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  9. MinMaxScaler — scikit-learn 1.7.0 documentation

    feature_range = (0, 1) , * , copy = True , clip = False ) [source]...X_std = ( X - X . min ( axis = 0 )) / ( X . max ( axis = 0 ) -...
    scikit-learn.org/stable/modules/generated/sklearn.preprocessing.MinMaxScaler.html
    Wed Jul 02 18:21:48 UTC 2025
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  10. FixedThresholdClassifier — scikit-learn 1.7.0 d...

    threshold = 'auto' , pos_label = None , response_method = 'auto'...weights = [ 0.9 , 0.1 ], class_sep = 0.8 , random_state = 42 ......
    scikit-learn.org/stable/modules/generated/sklearn.model_selection.FixedThresholdClassifier.html
    Wed Jul 02 18:21:48 UTC 2025
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