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1.7. Gaussian Processes — scikit-learn 1....
log-transformed [[ -inf 2.30258509] [ -inf 2.30258509] [ -inf 2.30258509]]...\left(1 + \frac{d(x_i, x_j)^2}{2\alpha l^2}\right)^{-\alpha}\] The...scikit-learn.org/stable/modules/gaussian_process.html -
Memory Configuration
export FESS_HEAP_SIZE = 2 g Units: m : megabytes g : gigabytes.../etc/sysconfig/fess . FESS_HEAP_SIZE = 2 g For DEB packages, edit /etc/default/fess...fess.codelibs.org/15.3/config/setup-memory.html -
make_sparse_uncorrelated — scikit-learn 1...
0 ] + 2 * X [:, 1 ] - 2 * X [:, 2 ] - 1.5 * X [:, 3...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_sparse_uncorrelated.html -
Illustration of Gaussian process classification...
2 ) Y = np . logical_xor ( X [:,...DotProduct ( sigma_0 = 1.0 ) ** 2 ] for i , kernel in enumerate...scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpc_xor.html -
BaggingRegressor — scikit-learn 1.8.0 doc...
float \(R^2\) of self.predict(X) w.r.t. y . Notes The \(R^2\) score...the method is known as Bagging [2] . When random subsets of the...scikit-learn.org/stable/modules/generated/sklearn.ensemble.BaggingRegressor.html -
mutual_info_classif — scikit-learn 1.8.0 ...
[ 2 ] ( 1 , 2 ) A. Kraskov, H. Stogbauer...neighbors distances as described in [2] and [3] . Both methods are based...scikit-learn.org/stable/modules/generated/sklearn.feature_selection.mutual_info_classif.html -
Novelty detection with Local Outlier Factor (LO...
2 ) X_train = np . r_ [ X + 2 , X - 2 ] # Generate...randn ( 20 , 2 ) X_test = np . r_ [ X + 2 , X - 2 ] # Generate...scikit-learn.org/stable/auto_examples/neighbors/plot_lof_novelty_detection.html -
MultiTaskElasticNet — scikit-learn 1.8.0 ...
[ 2 , 2 ]], [[ 0 , 0 ], [ 1 , 1 ], [ 2 , 2 ]]) Multi...is: ( 1 / ( 2 * n_samples )) * || Y - XW || _Fro ^ 2 + alpha *...scikit-learn.org/stable/modules/generated/sklearn.linear_model.MultiTaskElasticNet.html -
LocallyLinearEmbedding — scikit-learn 1.8...
(n_components + 1) / 2 . see reference [2] modified : use the...n_neighbors = 5 , n_components = 2 , reg = 0.001 , eigen_solver =...scikit-learn.org/stable/modules/generated/sklearn.manifold.LocallyLinearEmbedding.html -
RobustScaler — scikit-learn 1.8.0 documen...
- 2. , 2. ], ... [ - 2. , 1. , 3. ], ... [ 4. , 1. , - 2. ]]...transform ( X ) array([[ 0. , -2. , 0. ], [-1. , 0. , 0.4], [ 1....scikit-learn.org/stable/modules/generated/sklearn.preprocessing.RobustScaler.html