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Multioutput methods — scikit-learn 1.7.2 docume...
top Ctrl + K GitHub Choose version Multioutput methods # Examples...concerning the sklearn.multioutput module. Multilabel classification...scikit-learn.org/stable/auto_examples/multioutput/index.html -
Contributing — scikit-learn 1.7.2 documentation
git@github.com:YourLogin/scikit-learn.git # add --depth 1 if your...n/scikit-learn.git (push) upstream git@github.com:scikit-learn/scikit-learn.git...scikit-learn.org/stable/developers/contributing.html -
SVC — scikit-learn 1.7.2 documentation
kernel {‘linear’, ‘poly’, ‘rbf’, ‘sigmoid’, ‘precomputed’} or callable,...( * , C = 1.0 , kernel = 'rbf' , degree = 3 , gamma = 'scale'...scikit-learn.org/stable/modules/generated/sklearn.svm.SVC.html -
MinMaxScaler — scikit-learn 1.7.2 documentation
transform ( data )) [[0. 0. ] [0.25 0.25] [0.5 0.5 ] [1. 1. ]] >>>...X_std = ( X - X . min ( axis = 0 )) / ( X . max ( axis = 0 ) - X ....scikit-learn.org/stable/modules/generated/sklearn.preprocessing.MinMaxScaler.html -
RobustScaler — scikit-learn 1.7.2 documentation
, 2. ], ... [ - 2. , 1. , 3. ], ... [ 4. , 1. , - 2. ]] >>> transformer...transformer . transform ( X ) array([[ 0. , -2. , 0. ], [-1. , 0. , 0.4],...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.RobustScaler.html -
Normalizer — scikit-learn 1.7.2 documentation
4, 0.4], [0.1, 0.3, 0.9, 0.3], [0.5, 0.7, 0.5, 0.1]]) fit ( X...generated: ["x0", "x1", ..., "x(n_features_in_ - 1)"] . If input_features...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.Normalizer.html -
QuantileTransformer — scikit-learn 1.7.2 docume...
generated: ["x0", "x1", ..., "x(n_features_in_ - 1)"] . If input_features...normal ( loc = 0.5 , scale = 0.25 , size = ( 25 , 1 )), axis =...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.QuantileTransformer.html -
QuantileRegressor — scikit-learn 1.7.2 document...
intercept. solver {‘highs-ds’, ‘highs-ipm’, ‘highs’, ‘interior-point’,...<= reg . predict ( X )) np.float64(0.8) fit ( X , y , sample_weight...scikit-learn.org/stable/modules/generated/sklearn.linear_model.QuantileRegressor.html -
plot_discretization_strategies.rst.txt
meshgrid( np.linspace(X[:, 0].min(), X[:, 0].max(), 300), np.linspace(X[:,...len(strategies) + 1, i) ax.scatter(X[:, 0], X[:, 1], edgecolors="k") if ds_cnt...scikit-learn.org/stable/_sources/auto_examples/preprocessing/plot_discretization_strategies.rst.txt -
7.2. Feature extraction — scikit-learn 1.7.2 do...
() array([[ 1., 0., 0., 33.], [ 0., 1., 0., 12.], [ 0., 0., 1.,...1.000e+00, 2.003e+03], [1.000e+00, 0.000e+00, 1.000e+00, 0.000e+00,...scikit-learn.org/stable/modules/feature_extraction.html