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TransformedTargetRegressor — scikit-learn 1.5.2...
reshape ( - 1 , 1 ) >>> y = np . exp ( 2 * X )...all strings. Added in version 1.0. See also sklearn.preproces...scikit-learn.org/stable/modules/generated/sklearn.compose.TransformedTargetRegressor.html -
11.1. Array API support (experimental) — scikit...
1.1.1. PyTorch Support # PyTorch Tensors...scikit-learn’s estimators. 11.1.1. Example usage # Here is an example...scikit-learn.org/stable/modules/array_api.html -
ExpSineSquared — scikit-learn 1.5.2 documentation
ExpSineSquared ( length_scale = 1.0 , periodicity = 1.0 , length_scale_bounds...ExpSineSquared ( length_scale = 1 , periodicity = 1 ) >>> gpr = GaussianProcessRegre...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.ExpSineSquared.html -
empirical_covariance — scikit-learn 1.5.2 docum...
>>> X = [[ 1 , 1 , 1 ],[ 1 , 1 , 1 ],[ 1 , 1 , 1 ], ... [ 0 ,...scikit-learn.org/stable/modules/generated/sklearn.covariance.empirical_covariance.html -
KernelDensity — scikit-learn 1.5.2 documentation
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 -
quantile_transform — scikit-learn 1.5.2 documen...
otherwise (if 1) transform each sample. n_quantiles...subsample=None . Added in version 1.5: The option None to disable...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.quantile_transform.html -
RBF — scikit-learn 1.5.2 documentation
return_X_y = True ) >>> kernel = 1.0 * RBF ( 1.0 ) >>> gpc = GaussianProcessClass...ernels. RBF ( length_scale = 1.0 , length_scale_bounds = (1e-05,...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.RBF.html -
pairwise_distances — scikit-learn 1.5.2 documen...
[ 1 , 1 , 1 ]] >>> Y = [[ 1 , 0 , 0 ], [ 1 , 1 , 0 ]] >>>...deprecated from SciPy 1.9 and will be removed in SciPy 1.11. Note 'matching'...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise_distances.html -
8.1. Strategies to scale computationally: bigge...
1.1.1. Streaming instances # Basically, 1. may be a...to make your system scale. 8.1.1. Scaling with instances using...scikit-learn.org/stable/computing/scaling_strategies.html -
lasso_path — scikit-learn 1.5.2 documentation
alpha * || w || _1 For multi-output tasks it is: ( 1 / ( 2 * n_samples...lasso_path >>> X = np . array ([[ 1 , 2 , 3.1 ], [ 2.3 , 5.4 , 4.3 ]])...scikit-learn.org/stable/modules/generated/sklearn.linear_model.lasso_path.html