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  1. ExtraTreesClassifier — scikit-learn 1.6.1 docum...

    [{0: 1, 1: 1}, {0: 1, 1: 5}, {0: 1, 1: 1}, {0: 1, 1: 1}] instead...instead of [{1:1}, {2:5}, {3:1}, {4:1}]. The “balanced” mode uses...
    scikit-learn.org/stable/modules/generated/sklearn.ensemble.ExtraTreesClassifier.html
    Sat Apr 19 00:31:20 UTC 2025
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  2. Hyperparameter — scikit-learn 1.6.1 documentation

    n_elements = 1 , fixed = None ) [source] # A...the parameter. If n_elements>1, a pair of 1d array with n_elements...
    scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.Hyperparameter.html
    Sat Apr 19 00:31:20 UTC 2025
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  3. MultiTaskLasso — scikit-learn 1.6.1 documentation

    1 ) >>> clf . fit ([[ 0 , 1 ], [ 1 , 2 ], [ 2 ,...0 ], [ 1 , 1 ], [ 2 , 3 ]]) MultiTaskLasso(alpha=0.1) >>> print...
    scikit-learn.org/stable/modules/generated/sklearn.linear_model.MultiTaskLasso.html
    Sat Apr 19 00:31:21 UTC 2025
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  4. RandomForestClassifier — scikit-learn 1.6.1 doc...

    [{0: 1, 1: 1}, {0: 1, 1: 5}, {0: 1, 1: 1}, {0: 1, 1: 1}] instead...instead of [{1:1}, {2:5}, {3:1}, {4:1}]. The “balanced” mode uses...
    scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestClassifier.html
    Sat Apr 19 00:31:22 UTC 2025
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  5. RegressorMixin — scikit-learn 1.6.1 documentation

    array ([ - 1 , 0 , 1 ]) >>> estimator . fit ( X...__init__ ( self , * , param = 1 ): ... self . param = param ......
    scikit-learn.org/stable/modules/generated/sklearn.base.RegressorMixin.html
    Sat Apr 19 00:31:20 UTC 2025
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  6. ClassifierChain — scikit-learn 1.6.1 documentation

    X_test ) array([[1., 1., 0.], [1., 0., 0.], [0., 1., 0.]]) >>> chain...order = [ 0 , 1 , 2 , ... , Y . shape [ 1 ] - 1 ] The order of...
    scikit-learn.org/stable/modules/generated/sklearn.multioutput.ClassifierChain.html
    Sat Apr 19 00:31:20 UTC 2025
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  7. GaussianProcessRegressor — scikit-learn 1.6.1 d...

    ConstantKernel(1.0, constant_value_bounds="fixed") * RBF(1.0, lengt...implementation is based on Algorithm 2.1 of [RW2006] . In addition to standard...
    scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.GaussianProcessRegressor.html
    Sat Apr 19 00:31:21 UTC 2025
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  8. SGDOneClassSVM — scikit-learn 1.6.1 documentation

    array ([[ - 1 , - 1 ], [ - 2 , - 1 ], [ 1 , 1 ], [ 2 , 1 ]]) >>>...labels for X. Returns -1 for outliers and 1 for inliers. Parameters...
    scikit-learn.org/stable/modules/generated/sklearn.linear_model.SGDOneClassSVM.html
    Sat Apr 19 00:31:21 UTC 2025
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  9. RandomForestRegressor — scikit-learn 1.6.1 docu...

    min_samples_leaf = 1 , min_weight_fraction_leaf = 0.0 , max_features = 1.0 ,...e.g. 0.3. Changed in version 1.1: The default of max_features...
    scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestRegressor.html
    Sat Apr 19 00:31:20 UTC 2025
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  10. FunctionTransformer — scikit-learn 1.6.1 docume...

    Added in version 1.1. kw_args dict, default=None Dictionary...array([[0. , 0.6931...], [1.0986..., 1.3862...]]) fit ( X , y =...
    scikit-learn.org/stable/modules/generated/sklearn.preprocessing.FunctionTransformer.html
    Sat Apr 19 00:31:21 UTC 2025
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