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sklearn.gaussian_process — scikit-learn 1.5.2 d...
takes two kernels \(k_1\) and \(k_2\) and combines them via kernels.RBF...takes two kernels \(k_1\) and \(k_2\) and combines them via kernels.WhiteKernel...scikit-learn.org/stable/api/sklearn.gaussian_process.html -
ledoit_wolf_shrinkage — scikit-learn 1.5.2 docu...
2 ], [ .2 , .8 ]]) >>> rng = np . random...scikit-learn.org/stable/modules/generated/sklearn.covariance.ledoit_wolf_shrinkage.html -
FAQ on Elastic License 2.0 (ELv2) | Elastic
the Elastic License 2.0? The Elastic License 2.0 applies to our...content FAQ on Elastic License 2.0 (ELv2) Can you summarize what...www.elastic.co/licensing/elastic-license/faq -
DistanceMetric — scikit-learn 1.5.2 documentation
HaversineDistance 2 arcsin(sqrt(sin^2(0.5*dx) + cos(x1)cos(x2)sin^2(0.5*dy)))...'euclidean' ) >>> X = [[ 1 , 2 ], [ 3 , 4 ], [ 5 , 6 ]] >>> Y...scikit-learn.org/stable/modules/generated/sklearn.metrics.DistanceMetric.html -
RadiusNeighborsRegressor — scikit-learn 1.5.2 d...
float \(R^2\) of self.predict(X) w.r.t. y . Notes The \(R^2\) score...'auto' , leaf_size = 30 , p = 2 , metric = 'minkowski' , metric_params...scikit-learn.org/stable/modules/generated/sklearn.neighbors.RadiusNeighborsRegressor.html -
LassoLars — scikit-learn 1.5.2 documentation
is: ( 1 / ( 2 * n_samples )) * || y - Xw ||^ 2_2 + alpha * ||...float \(R^2\) of self.predict(X) w.r.t. y . Notes The \(R^2\) score...scikit-learn.org/stable/modules/generated/sklearn.linear_model.LassoLars.html -
RidgeClassifier — scikit-learn 1.5.2 documentation
scikit-learn.org/stable/modules/generated/sklearn.linear_model.RidgeClassifier.html -
Lars — scikit-learn 1.5.2 documentation
float \(R^2\) of self.predict(X) w.r.t. y . Notes The \(R^2\) score...n_nonzero_coefs = 500 , eps = np.float64(2.220446049250313e-16) , copy_X...scikit-learn.org/stable/modules/generated/sklearn.linear_model.Lars.html -
Exponentiation — scikit-learn 1.5.2 documentation
2) is equivalent to using the **...** operator with RBF() ** 2 . Read more in the User Guide . Added...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.Exponentiation.html -
ParameterGrid — scikit-learn 1.5.2 documentation
{ 'a' : 2 , 'b' : True }, { 'a' : 2 , 'b' : False }])...>>> param_grid = { 'a' : [ 1 , 2 ], 'b' : [ True , False ]} >>>...scikit-learn.org/stable/modules/generated/sklearn.model_selection.ParameterGrid.html