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ParameterGrid — scikit-learn 1.7.1 documentation
'a' : 1 , 'b' : False }, ... { 'a' : 2 , 'b' : True }, { 'a' :...{ 'kernel' : 'rbf' , 'gamma' : 1 }, ... { 'kernel' : 'rbf' , 'gamma'...scikit-learn.org/stable/modules/generated/sklearn.model_selection.ParameterGrid.html -
RegressorTags — scikit-learn 1.7.1 documentation
n_informative=1, bias=5.0, noise=20, random_state=42) . The dataset...R2 of 0.5 on make_regression(n_samples=200, n_features=10, n_informative=1,...scikit-learn.org/stable/modules/generated/sklearn.utils.RegressorTags.html -
has_fit_parameter — scikit-learn 1.7.1 document...
has_fit_parameter ( SVC (), "sample_weight" ) True On this page...sklearn.utils.validation. has_fit_parameter ( estimator , parameter ) [source]...scikit-learn.org/stable/modules/generated/sklearn.utils.validation.has_fit_parameter.html -
sklearn.pipeline — scikit-learn 1.7.1 documenta...
top Ctrl + K GitHub Choose version sklearn.pipeline # Utilities...transforms and estimators. User guide. See the Pipelines and composite...scikit-learn.org/stable/api/sklearn.pipeline.html -
Tweedie regression on insurance claims — scikit...
Third-Party Liability Claims dataset. Parameters ---------- n_samples:...() * 0.8 p2 = ax . fill_between ( df_ . index , 0 , y_max * df_...scikit-learn.org/stable/auto_examples/linear_model/plot_tweedie_regression_insurance_claims.html -
13. Choosing the right estimator — scikit-learn...
number of... NO NO <10K samples <10K... <10K samples <10K... NO NO...NEXT TRY... TRY NEXT TRY... TRY NEXT TRY... TRY NEXT TRY... TRY NEXT...scikit-learn.org/stable/machine_learning_map.html -
RadiusNeighborsRegressor — scikit-learn 1.7.1 d...
RadiusNeighborsRegre(...) >>> print ( neigh . predict ([[ 1.5 ]])) [0.5] fit...{‘auto’, ‘ball_tree’, ‘kd_tree’, ‘brute’}, default=’auto’ Algorithm...scikit-learn.org/stable/modules/generated/sklearn.neighbors.RadiusNeighborsRegressor.html -
QuadraticDiscriminantAnalysis — scikit-learn 1....
np . array ([[ - 1 , - 1 ], [ - 2 , - 1 ], [ - 3 , - 2 ], [ 1...1 , 1 ], [ 2 , 1 ], [ 3 , 2 ]]) >>> y = np . array ([ 1 , 1 ,...scikit-learn.org/stable/modules/generated/sklearn.discriminant_analysis.QuadraticDiscriminantAnal... -
1.10. Decision Trees — scikit-learn 1.7.1 docum...
>>> clf . predict_proba ([[ 2. , 2. ]]) array([[0., 1.]]) DecisionTreeClassifi...[[ 0 , 0 ], [ 1 , 1 ]] >>> Y = [ 0 , 1 ] >>> clf = tree . DecisionTreeClassifi...scikit-learn.org/stable/modules/tree.html -
DistanceMetric — scikit-learn 1.7.1 documentation
pairwise ( X , Y ) array([[7.81..., 10.63...] [5.65..., 8.48...] [1.41...,...arcsin(sqrt(sin^2(0.5*dx) + cos(x1)cos(x2)sin^2(0.5*dy))) Metrics...scikit-learn.org/stable/modules/generated/sklearn.metrics.DistanceMetric.html