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Varying regularization in Multi-layer Perceptro...
A comparison of different values for regularization parameter ‘alpha’ on synthetic datasets. The plot shows that different alphas yield different decision functions. Alpha is a parameter for regula...scikit-learn.org/stable/auto_examples/neural_networks/plot_mlp_alpha.html -
1.7. Gaussian Processes — scikit-learn 1.7.2 do...
Gaussian Processes (GP) are a nonparametric supervised learning method used to solve regression and probabilistic classification problems. The advantages of Gaussian processes are: The prediction i...scikit-learn.org/stable/modules/gaussian_process.html -
Pipelining: chaining a PCA and a logistic regre...
The PCA does an unsupervised dimensionality reduction, while the logistic regression does the prediction. We use a GridSearchCV to set the dimensionality of the PCA, Total running time of the scrip...scikit-learn.org/stable/auto_examples/compose/plot_digits_pipe.html -
2.6. Covariance estimation — scikit-learn 1.7.2...
Many statistical problems require the estimation of a population’s covariance matrix, which can be seen as an estimation of data set scatter plot shape. Most of the time, such an estimation has to ...scikit-learn.org/stable/modules/covariance.html -
Lasso model selection via information criteria ...
This example reproduces the example of Fig. 2 of[ZHT2007]. A LassoLarsIC estimator is fit on a diabetes dataset and the AIC and the BIC criteria are used to select the best model. References ZHT200...scikit-learn.org/stable/auto_examples/linear_model/plot_lasso_lars_ic.html -
Recursive feature elimination with cross-valida...
A Recursive Feature Elimination (RFE) example with automatic tuning of the number of features selected with cross-validation. Data generation: We build a classification task using 3 informative fea...scikit-learn.org/stable/auto_examples/feature_selection/plot_rfe_with_cross_validation.html -
Explicit feature map approximation for RBF kern...
An example illustrating the approximation of the feature map of an RBF kernel. It shows how to use RBFSampler and Nystroem to approximate the feature map of an RBF kernel for classification with an...scikit-learn.org/stable/auto_examples/miscellaneous/plot_kernel_approximation.html -
Swiss Roll And Swiss-Hole Reduction — scikit-le...
This notebook seeks to compare two popular non-linear dimensionality techniques, T-distributed Stochastic Neighbor Embedding (t-SNE) and Locally Linear Embedding (LLE), on the classic Swiss Roll da...scikit-learn.org/stable/auto_examples/manifold/plot_swissroll.html -
Failure of Machine Learning to infer causal eff...
Machine Learning models are great for measuring statistical associations. Unfortunately, unless we’re willing to make strong assumptions about the data, those models are unable to infer causal effe...scikit-learn.org/stable/auto_examples/inspection/plot_causal_interpretation.html -
Effect of model regularization on training and ...
In this example, we evaluate the impact of the regularization parameter in a linear model called ElasticNet. To carry out this evaluation, we use a validation curve using ValidationCurveDisplay. Th...scikit-learn.org/stable/auto_examples/model_selection/plot_train_error_vs_test_error.html