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SplineTransformer — scikit-learn 1.5.2 document...
Must be larger or equal 2. Ignored if knots is array-like....scipy>=1.8 . Added in version 1.2. Attributes : bsplines_ list of...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.SplineTransformer.html -
FunctionTransformer — scikit-learn 1.5.2 docume...
then X will be converted to a 2-dimensional NumPy array or sparse...X = np . array ([[ 0 , 1 ], [ 2 , 3 ]]) >>> transformer . transform...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.FunctionTransformer.html -
RegressorChain — scikit-learn 1.5.2 documentation
2 ], [ 1 , 1 ], [ 2 , 0 ]] >>> chain = RegressorChain...predict ( X ) array([[0., 2.], [1., 1.], [2., 0.]]) fit ( X , Y ,...scikit-learn.org/stable/modules/generated/sklearn.multioutput.RegressorChain.html -
PLSSVD — scikit-learn 1.5.2 documentation
[ 2. , 2. , 2. ], ... [ 2. , 5. , 4. ]]) >>>...([[ 0.1 , - 0.2 ], ... [ 0.9 , 1.1 ], ... [ 6.2 , 5.9 ], ... [...scikit-learn.org/stable/modules/generated/sklearn.cross_decomposition.PLSSVD.html -
smacof — scikit-learn 1.5.2 documentation
2 ], [ 1 , 0 , 3 ],[ 2 , 3 , 0 ]]) >>> dissimilarities...metric = True , n_components = 2 , init = None , n_init = 8 , n_jobs...scikit-learn.org/stable/modules/generated/sklearn.manifold.smacof.html -
NeighborhoodComponentsAnalysis — scikit-learn 1...
ize will be set to verbose - 2 . random_state int or numpy.RandomState,...~roweis/papers/ncanips.pdf [ 2 ] Wikipedia entry on Neighborhood...scikit-learn.org/stable/modules/generated/sklearn.neighbors.NeighborhoodComponentsAnalysis.html -
Product — scikit-learn 1.5.2 documentation
takes two kernels \(k_1\) and \(k_2\) and combines them via \[k_{prod}(X,...\[k_{prod}(X, Y) = k_1(X, Y) * k_2(X, Y)\] Note that the __mul__ magic...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.Product.html -
make_regression — scikit-learn 1.5.2 documentation
n_features = 2 , noise = 1 , random_state = 42...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_regression.html -
trustworthiness — scikit-learn 1.5.2 documentation
defined as \[T(k) = 1 - \frac{2}{nk (2n - 3k - 1)} \sum^n_{i=1}...Should be fewer than n_samples / 2 to ensure the trustworthiness...scikit-learn.org/stable/modules/generated/sklearn.manifold.trustworthiness.html -
MinCovDet — scikit-learn 1.5.2 documentation
(n_samples + n_features + 1) / 2 * n_samples . The parameter must...scikit-learn.org/stable/modules/generated/sklearn.covariance.MinCovDet.html