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sklearn.pipeline — scikit-learn 1.6.1 documenta...
Utilities to build a composite estimator as a chain of transforms and estimators. User guide. See the Pipelines and composite estimators section for further details.scikit-learn.org/stable/api/sklearn.pipeline.html -
randomized_svd — scikit-learn 1.6.1 documentation
Skip to main content Back to top Ctrl + K GitHub Choose version randomized_svd # sklearn.utils.extmath. randomized_sv...scikit-learn.org/stable/modules/generated/sklearn.utils.extmath.randomized_svd.html -
all_estimators — scikit-learn 1.6.1 documentation
Skip to main content Back to top Ctrl + K GitHub Choose version all_estimators # sklearn.utils.discovery. all_estimat...scikit-learn.org/stable/modules/generated/sklearn.utils.discovery.all_estimators.html -
Generalized Linear Models — scikit-learn 1.6.1 ...
Examples concerning the sklearn.linear_model module. Comparing Linear Bayesian Regressors Comparing various online solvers Curve Fitting with Bayesian Ridge Regression Decision Boundaries of Multin...scikit-learn.org/stable/auto_examples/linear_model/index.html -
Gradient Boosting regression — scikit-learn 1.6...
This example demonstrates Gradient Boosting to produce a predictive model from an ensemble of weak predictive models. Gradient boosting can be used for regression and classification problems. Here,...scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_regression.html -
Pipelines and composite estimators — scikit-lea...
Examples of how to compose transformers and pipelines from other estimators. See the User Guide. Column Transformer with Heterogeneous Data Sources Column Transformer with Mixed Types Concatenating...scikit-learn.org/stable/auto_examples/compose/index.html -
SVM Margins Example — scikit-learn 1.6.1 docume...
The plots below illustrate the effect the parameter C has on the separation line. A large value of C basically tells our model that we do not have that much faith in our data’s distribution, and wi...scikit-learn.org/stable/auto_examples/svm/plot_svm_margin.html -
Recursive feature elimination — scikit-learn 1....
This example demonstrates how Recursive Feature Elimination ( RFE) can be used to determine the importance of individual pixels for classifying handwritten digits. RFE recursively removes the least...scikit-learn.org/stable/auto_examples/feature_selection/plot_rfe_digits.html -
Polynomial and Spline interpolation — scikit-le...
This example demonstrates how to approximate a function with polynomials up to degree degree by using ridge regression. We show two different ways given n_samples of 1d points x_i: PolynomialFeatur...scikit-learn.org/stable/auto_examples/linear_model/plot_polynomial_interpolation.html -
SGD: Penalties — scikit-learn 1.6.1 documentation
Contours of where the penalty is equal to 1 for the three penalties L1, L2 and elastic-net. All of the above are supported by SGDClassifier and SGDRegressor. Total running time of the script:(0 min...scikit-learn.org/stable/auto_examples/linear_model/plot_sgd_penalties.html