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Concatenating multiple feature extraction metho...
In many real-world examples, there are many ways to extract features from a dataset. Often it is beneficial to combine several methods to obtain good performance. This example shows how to use Feat...scikit-learn.org/stable/auto_examples/compose/plot_feature_union.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 -
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 -
Effect of transforming the targets in regressio...
In this example, we give an overview of TransformedTargetRegressor. We use two examples to illustrate the benefit of transforming the targets before learning a linear regression model. The first ex...scikit-learn.org/stable/auto_examples/compose/plot_transformed_target.html -
Compare Stochastic learning strategies for MLPC...
This example visualizes some training loss curves for different stochastic learning strategies, including SGD and Adam. Because of time-constraints, we use several small datasets, for which L-BFGS ...scikit-learn.org/stable/auto_examples/neural_networks/plot_mlp_training_curves.html -
Test with permutations the significance of a cl...
This example demonstrates the use of permutation_test_score to evaluate the significance of a cross-validated score using permutations. Dataset: We will use the Iris plants dataset, which consists ...scikit-learn.org/stable/auto_examples/model_selection/plot_permutation_tests_for_classification.html -
1.14. Semi-supervised learning — scikit-learn 1...
Semi-supervised learning is a situation in which in your training data some of the samples are not labeled. The semi-supervised estimators in sklearn.semi_supervised are able to make use of this ad...scikit-learn.org/stable/modules/semi_supervised.html -
2.7. Novelty and Outlier Detection — scikit-lea...
Many applications require being able to decide whether a new observation belongs to the same distribution as existing observations (it is an inlier), or should be considered as different (it is an ...scikit-learn.org/stable/modules/outlier_detection.html -
Linear and Quadratic Discriminant Analysis with...
This example plots the covariance ellipsoids of each class and the decision boundary learned by LinearDiscriminantAnalysis(LDA) and QuadraticDiscriminantAnalysis(QDA). The ellipsoids display the do...scikit-learn.org/stable/auto_examples/classification/plot_lda_qda.html -
Release Highlights for scikit-learn 1.3 — sciki...
We are pleased to announce the release of scikit-learn 1.3! Many bug fixes and improvements were added, as well as some new key features. We detail below a few of the major features of this release...scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_3_0.html