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Sum — scikit-learn 1.5.2 documentation
Skip to main content Back to top Ctrl + K GitHub Sum # class sklearn.gaussian_process.kernels. Sum ( k1 , k2 ) [sourc...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.Sum.html -
DotProduct — scikit-learn 1.5.2 documentation
Gallery examples: Illustration of Gaussian process classification (GPC) on the XOR dataset Illustration of prior and posterior Gaussian process for different kernels Iso-probability lines for Gauss...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.DotProduct.html -
Kernel — scikit-learn 1.5.2 documentation
Gallery examples: Gaussian processes on discrete data structuresscikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.Kernel.html -
GaussianProcessRegressor — scikit-learn 1.5.2 d...
Gallery examples: Ability of Gaussian process regression (GPR) to estimate data noise-level Comparison of kernel ridge and Gaussian process regression Forecasting of CO2 level on Mona Loa dataset u...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.GaussianProcessRegressor.html -
Lasso — scikit-learn 1.5.2 documentation
Gallery examples: Release Highlights for scikit-learn 1.4 Release Highlights for scikit-learn 0.23 Compressive sensing: tomography reconstruction with L1 prior (Lasso) Joint feature selection with ...scikit-learn.org/stable/modules/generated/sklearn.linear_model.Lasso.html -
Ridge — scikit-learn 1.5.2 documentation
Gallery examples: Compressive sensing: tomography reconstruction with L1 prior (Lasso) Prediction Latency Comparison of kernel ridge and Gaussian process regression HuberRegressor vs Ridge on datas...scikit-learn.org/stable/modules/generated/sklearn.linear_model.Ridge.html -
RBF — scikit-learn 1.5.2 documentation
Gallery examples: Classifier comparison Plot classification probability Ability of Gaussian process regression (GPR) to estimate data noise-level Comparison of kernel ridge and Gaussian process reg...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.RBF.html -
TimeSeriesSplit — scikit-learn 1.5.2 documentation
Gallery examples: Features in Histogram Gradient Boosting Trees Lagged features for time series forecasting Time-related feature engineering L1-based models for Sparse Signals Visualizing cross-val...scikit-learn.org/stable/modules/generated/sklearn.model_selection.TimeSeriesSplit.html -
SplineTransformer — scikit-learn 1.5.2 document...
Gallery examples: Release Highlights for scikit-learn 1.0 Time-related feature engineering Polynomial and Spline interpolation Evaluation of outlier detection estimatorsscikit-learn.org/stable/modules/generated/sklearn.preprocessing.SplineTransformer.html -
PowerTransformer — scikit-learn 1.5.2 documenta...
Gallery examples: Compare the effect of different scalers on data with outliers Map data to a normal distributionscikit-learn.org/stable/modules/generated/sklearn.preprocessing.PowerTransformer.html