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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 -
MiniBatchNMF — scikit-learn 1.8.0 documen...
||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.MiniBatchNMF.html -
L1-based models for Sparse Signals — scik...
linspace ( - 2 , 2 , n_samples ) freqs = 2 * np . pi * np ....time_step + 2 * ( rng . random_sample () - 0.5 )) X [:, i ] += 0.2 * rng...scikit-learn.org/stable/auto_examples/linear_model/plot_lasso_and_elasticnet.html -
randomized_svd — scikit-learn 1.8.0 docum...
2), (2,), (2, 4)) On this page This Page...increase this parameter up to 2*k - n_components where k is the...scikit-learn.org/stable/modules/generated/sklearn.utils.extmath.randomized_svd.html -
trustworthiness — scikit-learn 1.8.0 docu...
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 -
HuberRegressor vs Ridge on dataset with strong ...
2.0 , size = 4 ) X_outliers [: 2 , :] += X . max...y_outliers [: 2 ] += y . min () - y . mean () / 4.0 y_outliers [ 2 :] +=...scikit-learn.org/stable/auto_examples/linear_model/plot_huber_vs_ridge.html -
7.3. Preprocessing data — scikit-learn 1....
2. , 1. , 0.1], [4.4, 2.2, 1.1, 0.1], [4.4, 2.2, 1.2, 0.1],...4.1, 6.7, 2.5], [7.7, 4.2, 6.7, 2.5], [7.9, 4.4, 6.9, 2.5]]) Thus...scikit-learn.org/stable/modules/preprocessing.html -
DBSCAN — scikit-learn 1.8.0 documentation
2 ], [ 2 , 2 ], [ 2 , 3 ], ... [ 8 , 7 ],...memory complexity of \(O({n}^2)\) , which can occur when the...scikit-learn.org/stable/modules/generated/sklearn.cluster.DBSCAN.html -
TheilSenRegressor — scikit-learn 1.8.0 do...
float \(R^2\) of self.predict(X) w.r.t. y . Notes The \(R^2\) score...n_samples = 200 , n_features = 2 , noise = 4.0 , random_state =...scikit-learn.org/stable/modules/generated/sklearn.linear_model.TheilSenRegressor.html -
plot_classifier_comparison.rst.txt
make_classification( n_features=2, n_redundant=0, n_informative=2, random_state=1,...rng = np.random.RandomState(2) X += 2 * rng.uniform(size=X.shape)...scikit-learn.org/stable/_sources/auto_examples/classification/plot_classifier_comparison.rst.txt