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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 -
Plot multi-class SGD on the iris dataset —...
Plot decision surface of multi-class SGD on iris dataset. The hyperplanes corresponding to the three one-versus-all (OVA) classifiers are represented by the dashed lines. Total running time of the ...scikit-learn.org/stable/auto_examples/linear_model/plot_sgd_iris.html -
Gaussian process classification (GPC) on iris d...
This example illustrates the predicted probability of GPC for an isotropic and anisotropic RBF kernel on a two-dimensional version for the iris-dataset. The anisotropic RBF kernel obtains slightly ...scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpc_iris.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 -
Novelty detection with Local Outlier Factor (LO...
The Local Outlier Factor (LOF) algorithm is an unsupervised anomaly detection method which computes the local density deviation of a given data point with respect to its neighbors. It considers as ...scikit-learn.org/stable/auto_examples/neighbors/plot_lof_novelty_detection.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 -
Visualizing cross-validation behavior in scikit...
Choosing the right cross-validation object is a crucial part of fitting a model properly. There are many ways to split data into training and test sets in order to avoid model overfitting, to stand...scikit-learn.org/stable/auto_examples/model_selection/plot_cv_indices.html -
Comparing Random Forests and Histogram Gradient...
In this example we compare the performance of Random Forest (RF) and Histogram Gradient Boosting (HGBT) models in terms of score and computation time for a regression dataset, though all the concep...scikit-learn.org/stable/auto_examples/ensemble/plot_forest_hist_grad_boosting_comparison.html -
Plot the decision surfaces of ensembles of tree...
Plot the decision surfaces of forests of randomized trees trained on pairs of features of the iris dataset. This plot compares the decision surfaces learned by a decision tree classifier (first col...scikit-learn.org/stable/auto_examples/ensemble/plot_forest_iris.html -
Model selection with Probabilistic PCA and Fact...
Probabilistic PCA and Factor Analysis are probabilistic models. The consequence is that the likelihood of new data can be used for model selection and covariance estimation. Here we compare PCA and...scikit-learn.org/stable/auto_examples/decomposition/plot_pca_vs_fa_model_selection.html