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scale — scikit-learn 1.8.0 documentation
independently array([[-1., 1., 1.], [ 1., -1., -1.]]) >>>...>>> X = [[ - 2 , 1 , 2 ], [ - 1 , 0 , 1 ]] >>> scale...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.scale.html -
KernelDensity — scikit-learn 1.8.0 docume...
log_density array([-1.52955942, -1.51462041, -1.60244657]) fit (...KernelDensity ( * , bandwidth = 1.0 , algorithm = 'auto' , kernel...scikit-learn.org/stable/modules/generated/sklearn.neighbors.KernelDensity.html -
det_curve — scikit-learn 1.8.0 documentation
y_true is in {-1, 1} or {0, 1}, pos_label is set to 1, otherwise...labels are not either {-1, 1} or {0, 1}, then pos_label should...scikit-learn.org/stable/modules/generated/sklearn.metrics.det_curve.html -
coverage_error — scikit-learn 1.8.0 docum...
>>> y_true = [[ 1 , 0 , 0 ], [ 0 , 1 , 1 ]] >>> y_score...y_score = [[ 1 , 0 , 0 ], [ 0 , 1 , 1 ]] >>> coverage_error...scikit-learn.org/stable/modules/generated/sklearn.metrics.coverage_error.html -
additive_chi2_kernel — scikit-learn 1.8.0...
[ 1 , 1 , 1 ]] >>> Y = [[ 1 , 0 , 0 ], [ 1 , 1 , 0...additive_chi2_kernel ( X , Y ) array([[-1., -2.], [-2., -1.]]) On this page This...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.additive_chi2_kernel.html -
Successive Halving Iterations — scikit-le...
[{0: 1, 1: 1}, {0: 1, 1: 5}, {0: 1, 1: 1}, {0: 1, 1: 1}] instead...[{0: 1, 1: 1}, {0: 1, 1: 5}, {0: 1, 1: 1}, {0: 1, 1: 1}] instead...scikit-learn.org/stable/auto_examples/model_selection/plot_successive_halving_iterations.html -
KNeighborsTransformer — scikit-learn 1.8....
() array([[1., 0., 1.], [0., 1., 1.], [1., 0., 1.]]) set_output...rs=1) >>> print ( neigh . kneighbors ([[ 1. , 1. , 1....scikit-learn.org/stable/modules/generated/sklearn.neighbors.KNeighborsTransformer.html -
make_friedman1 — scikit-learn 1.8.0 docum...
Annals of Statistics 19 (1), pages 1-67, 1991. [ 2 ] L. Breiman,...[source] # Generate the “Friedman #1” regression problem. This dataset...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_friedman1.html -
2.3. Clustering — scikit-learn 1.8.0 docu...
1 , 1 , 1 ] >>> labels_pred = [ 0 , 0 , 1 , 1 , 2...0 , 1 , 1 , 1 ] >>> labels_pred = [ 0 , 0 , 1 , 1 , 2...scikit-learn.org/stable/modules/clustering.html -
RadiusNeighborsRegressor — scikit-learn 1...
() array([[1., 0., 1.], [0., 1., 0.], [1., 0., 1.]]) score (...], [ 1 ], [ 2 ], [ 3 ]] >>> y = [ 0 , 0 , 1 , 1 ] >>>...scikit-learn.org/stable/modules/generated/sklearn.neighbors.RadiusNeighborsRegressor.html