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ExpSineSquared — scikit-learn 1.8.0 docum...
\text{exp}\left(- \frac{ 2\sin^2(\pi d(x_i, x_j)/p) }{ l^ 2} \right)\] where...>>> gpr . predict ( X [: 2 ,:], return_std = True ) (array([425.6,...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.ExpSineSquared.html -
Ridge coefficients as a function of the L2 Regu...
- X \beta \|^{2}_{2} + \alpha \| \beta \|^{2}_{2}\) where \(X\)...side (e.g. \(\|y - X\beta\|^{2}_{2}\) ) measures the squared difference...scikit-learn.org/stable/auto_examples/linear_model/plot_ridge_coeffs.html -
grid_search.rst.txt
+--------- | 3 * 2 = 6 | 70 // 2 = 35 | +--------- | 6 * 2 = 12 | 35...35 // 2 = 17 | +--------- | 12 * 2 = 24 | 17 // 2 = 8 | +---------...scikit-learn.org/stable/_sources/modules/grid_search.rst.txt -
Label Propagation digits: Active learning ̵...
0 24 0] [ 0 0 0 0 2 1 0 2 2 27]] Iteration 2 __________ Label...0 0 0 0 0 25 0] [ 0 0 0 0 2 1 0 2 2 27]] Iteration 1 __________...scikit-learn.org/stable/auto_examples/semi_supervised/plot_label_propagation_digits_active_learni... -
Spring - IBM Developer
of 2 pages 1 2 of 2 pages Previous page Next...Java applications for CICS, Part 2: Security Explore three different...developer.ibm.com/components/spring -
Robust vs Empirical covariance estimate —...
subplot ( 2 , 1 , 1 ) lw = 2 plt . errorbar ( range_n_outliers...font_prop ) plt . subplot ( 2 , 1 , 2 ) x_size = range_n_outliers...scikit-learn.org/stable/auto_examples/covariance/plot_robust_vs_empirical_covariance.html -
RadiusNeighborsRegressor — scikit-learn 1...
float \(R^2\) of self.predict(X) w.r.t. y . Notes The \(R^2\) score...'auto' , leaf_size = 30 , p = 2 , metric = 'minkowski' , metric_params...scikit-learn.org/stable/modules/generated/sklearn.neighbors.RadiusNeighborsRegressor.html -
ensemble.rst.txt
features 1 and 2. But note that features 0 and 2 are forbidden...Right split at feature 2 has only group {1, 2} from now on. LightGBM...scikit-learn.org/stable/_sources/modules/ensemble.rst.txt -
OrdinalEncoder — scikit-learn 1.8.0 docum...
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 -
BaseEstimator — scikit-learn 1.8.0 docume...
{'param': 2} >>> X = np . array ([[ 1 , 2 ], [ 2 , 3 ],...y ) . predict ( X ) array([2, 2, 2]) >>> estimator ....scikit-learn.org/stable/modules/generated/sklearn.base.BaseEstimator.html