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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 -
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 -
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 -
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 -
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 -
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 -
3.1. Cross-validation: evaluating estimator per...
Learning the parameters of a prediction function and testing it on the same data is a methodological mistake: a model that would just repeat the labels of the samples that it has just seen would ha...scikit-learn.org/stable/modules/cross_validation.html -
3.3. Tuning the decision threshold for class pr...
Classification is best divided into two parts: the statistical problem of learning a model to predict, ideally, class probabilities;, the decision problem to take concrete action based on those pro...scikit-learn.org/stable/modules/classification_threshold.html -
Lasso model selection: AIC-BIC / cross-validati...
This example focuses on model selection for Lasso models that are linear models with an L1 penalty for regression problems. Indeed, several strategies can be used to select the value of the regular...scikit-learn.org/stable/auto_examples/linear_model/plot_lasso_model_selection.html