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ElasticNetCV — scikit-learn 1.7.2 documentation
objective is: 1 / ( 2 * n_samples ) * || y - Xw ||^ 2_2 + alpha * l1_ratio...it is: 1 / ( 2 * n_samples ) * || y - Xw ||^ 2_2 + alpha * l1_ratio...scikit-learn.org/stable/modules/generated/sklearn.linear_model.ElasticNetCV.html -
PowerTransformer — scikit-learn 1.7.2 documenta...
2 ], [ 3 , 2 ], [ 4 , 5 ]] >>> print...0 and lambda_ != 2 : X_original = 1 - ( - ( 2 - lambda_ ) * X...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.PowerTransformer.html -
CCA — scikit-learn 1.7.2 documentation
[ 2. , 2. , 2. ], [ 3. , 5. , 4. ]] >>>...y = [[ 0.1 , - 0.2 ], [ 0.9 , 1.1 ], [ 6.2 , 5.9 ], [ 11.9 ,...scikit-learn.org/stable/modules/generated/sklearn.cross_decomposition.CCA.html -
VotingRegressor — scikit-learn 1.7.2 documentation
float \(R^2\) of self.predict(X) w.r.t. y . Notes The \(R^2\) score...X = np . array ([[ 1 , 1 ], [ 2 , 4 ], [ 3 , 9 ], [ 4 , 16 ],...scikit-learn.org/stable/modules/generated/sklearn.ensemble.VotingRegressor.html -
NMF — scikit-learn 1.7.2 documentation
||H||_{Fro}^2,\end{aligned}\end{align} \] where \(||A||_{Fro}^2 = \sum_{i,j}...array ([[ 1 , 1 ], [ 2 , 1 ], [ 3 , 1.2 ], [ 4 , 1 ], [ 5 , 0.8...scikit-learn.org/stable/modules/generated/sklearn.decomposition.NMF.html -
RBF — scikit-learn 1.7.2 documentation
x_j)^2}{2l^2} \right)\] where \(l\) is the...very smooth. See [2] , Chapter 4, Section 4.2, for further details...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.RBF.html -
LocalOutlierFactor — scikit-learn 1.7.2 documen...
array([[2]])) As you can see, it returns [[0.5]], and [[2]], which..., metric = 'minkowski' , p = 2 , metric_params = None , contamination...scikit-learn.org/stable/modules/generated/sklearn.neighbors.LocalOutlierFactor.html -
DotProduct — scikit-learn 1.7.2 documentation
\sigma_0^2)\) on the bias. The DotProduct...of the kernel. For \(\sigma_0^2 =0\) , the kernel is called the...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.DotProduct.html -
OrdinalEncoder — scikit-learn 1.7.2 documentation
transform ( X_test ) array([[2.], [0.], [1.], [2.], [3.], [4.]]) fit (...scikit-learn 1.2 Release Highlights for scikit-learn 1.2 Release Highlights...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.OrdinalEncoder.html -
ExpSineSquared — scikit-learn 1.7.2 documentation
\text{exp}\left(- \frac{ 2\sin^2(\pi d(x_i, x_j)/p) }{ l^ 2} \right)\] where...0.0144 >>> gpr . predict ( X [: 2 ,:], return_std = True ) (array([425.6,...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.ExpSineSquared.html