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Sum — scikit-learn 1.8.0 documentation
kernel = Sum ( ConstantKernel ( 2 ), RBF ()) >>> gpr = GaussianProcessRegre...X , y ) 1.0 >>> kernel 1.41**2 + RBF(length_scale=1) __call__...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.Sum.html -
Gaussian Mixture Model Ellipsoids — scikit-lear...
eigh ( covar ) v = 2.0 * np . sqrt ( 2.0 ) * np . sqrt ( v )...n_samples , 2 ), C ), 0.7 * np . random . randn ( n_samples , 2 ) + np...scikit-learn.org/stable/auto_examples/mixture/plot_gmm.html -
Product — scikit-learn 1.8.0 documentation
= Product ( ConstantKernel ( 2 ), RBF ()) >>> gpr = GaussianProcessRegre...X , y ) 1.0 >>> kernel 1.41**2 * RBF(length_scale=1) __call__...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.Product.html -
ledoit_wolf — scikit-learn 1.8.0 documentation
2 ], [ .2 , .8 ]]) >>> rng = np . random...scikit-learn.org/stable/modules/generated/sklearn.covariance.ledoit_wolf.html -
plot_hgbt_regression.py
2. :ref:`categorical_support_gbdt`,...showcasing all points except 2 and 6 in a real life setting....scikit-learn.org/stable/_downloads/d108f2283ac3905eb623b32d42217a2b/plot_hgbt_regression.py -
Demonstration of multi-metric evaluation on cro...
"min_samples_split" : range ( 2 , 403 , 20 )}, scoring = scoring...scoring , refit = "AUC" , n_jobs = 2 , return_train_score = True ,...scikit-learn.org/stable/auto_examples/model_selection/plot_multi_metric_evaluation.html -
DictVectorizer — scikit-learn 1.8.0 documentation
'bar' : 2 }, { 'foo' : 3 , 'baz' : 1 }]...fit_transform ( D ) >>> X array([[2., 0., 1.], [0., 1., 3.]]) >>>...scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.DictVectorizer.html -
GaussianProcessRegressor — scikit-learn 1.8.0 d...
float \(R^2\) of self.predict(X) w.r.t. y . Notes The \(R^2\) score...implementation is based on Algorithm 2.1 of [RW2006] . In addition to...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.GaussianProcessRegressor.html -
IBM Maximo Application Suite - IBM Developer
of 2 pages 1 2 of 2 pages Previous page Next...developer.ibm.com/components/maximo -
RBF SVM parameters — scikit-learn 1.8.0 documen...
problem involving only 2 input features and 2 possible target classes...sub-sample the dataset to keep only 2 classes and make it a binary classification...scikit-learn.org/stable/auto_examples/svm/plot_rbf_parameters.html