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12. Dispatching — scikit-learn 1.8.0 documentation
1. Array API support (experimental) 12.1.1. Enabling...array API support 12.1.2. Example usage 12.1.3. Support for Array...scikit-learn.org/stable/dispatching.html -
9.3. Parallelism, resource management, and conf...
1.1. Higher-level parallelism with...management, and configuration # 9.3.1. Parallelism # Some scikit-learn...scikit-learn.org/stable/computing/parallelism.html -
2.6. Covariance estimation — scikit-learn 1.8.0...
1. Empirical covariance # The covariance...2.6.2. Shrunk Covariance # 2.6.2.1. Basic shrinkage # Despite being...scikit-learn.org/stable/modules/covariance.html -
1.14. Semi-supervised learning — scikit-learn 1...
Classification on a Text Dataset 1.14.1. Self Training # This self-training...Ctrl + K GitHub Choose version 1.14. Semi-supervised learning #...scikit-learn.org/stable/modules/semi_supervised.html -
5. Inspection — scikit-learn 1.8.0 documentation
1.1. Partial dependence plots 5.1.2. Individual...expectation (ICE) plot 5.1.3. Mathematical Definition 5.1.4. Computation...scikit-learn.org/stable/inspection.html -
Perceptron — scikit-learn 1.8.0 documentation
max_iter = 1000 , tol = 0.001 , shuffle = True , verbose = 0 , eta0...penalty = None , alpha = 0.0001 , l1_ratio = 0.15 , fit_intercept =...scikit-learn.org/stable/modules/generated/sklearn.linear_model.Perceptron.html -
linear_model.rst.txt
RidgeCV(alphas=array([1.e-06, 1.e-05, 1.e-04, 1.e-03, 1.e-02, 1.e-01, 1.e+00, 1.e+01,...1.e+01, 1.e+02, 1.e+03, 1.e+04, 1.e+05, 1.e+06])) >>> reg.alpha_...scikit-learn.org/stable/_sources/modules/linear_model.rst.txt -
LinearSVC — scikit-learn 1.8.0 documentation
intercept_ ) [0.1693] >>> print ( clf . predict ([[ 0 , 0 , 0 , 0 ]]))...dual = 'auto' , tol = 0.0001 , C = 1.0 , multi_class = 'ovr'...scikit-learn.org/stable/modules/generated/sklearn.svm.LinearSVC.html -
PolynomialFeatures — scikit-learn 1.8.0 documen...
fit_transform ( X ) array([[ 1., 0., 1., 0., 0., 1.], [ 1., 2., 3., 4., 6.,...) array([[ 1., 0., 1., 0.], [ 1., 2., 3., 6.], [ 1., 4., 5., 20.]])...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.PolynomialFeatures.html -
GammaRegressor — scikit-learn 1.8.0 documentation
float64(0.773) >>> clf . coef_ array([0.073, 0.067]) >>> clf...max_iter = 100 , tol = 0.0001 , warm_start = False , verbose = 0 ) [source]...scikit-learn.org/stable/modules/generated/sklearn.linear_model.GammaRegressor.html