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Factor Analysis (with rotation) to visualize pa...
Investigating the Iris dataset, we see that sepal length, petal length and petal width are highly correlated. Sepal width is less redundant. Matrix decomposition techniques can uncover these latent...scikit-learn.org/stable/auto_examples/decomposition/plot_varimax_fa.html -
Comparison of F-test and mutual information — s...
This example illustrates the differences between univariate F-test statistics and mutual information. We consider 3 features x_1, x_2, x_3 distributed uniformly over [0, 1], the target depends on t...scikit-learn.org/stable/auto_examples/feature_selection/plot_f_test_vs_mi.html -
Face completion with a multi-output estimators ...
This example shows the use of multi-output estimator to complete images. The goal is to predict the lower half of a face given its upper half. The first column of images shows true faces. The next ...scikit-learn.org/stable/auto_examples/miscellaneous/plot_multioutput_face_completion.html -
Comparison of kernel ridge regression and SVR —...
Both kernel ridge regression (KRR) and SVR learn a non-linear function by employing the kernel trick, i.e., they learn a linear function in the space induced by the respective kernel which correspo...scikit-learn.org/stable/auto_examples/miscellaneous/plot_kernel_ridge_regression.html -
Manifold Learning methods on a severed sphere —...
An application of the different Manifold learning techniques on a spherical data-set. Here one can see the use of dimensionality reduction in order to gain some intuition regarding the manifold lea...scikit-learn.org/stable/auto_examples/manifold/plot_manifold_sphere.html -
SVM: Separating hyperplane for unbalanced class...
Find the optimal separating hyperplane using an SVC for classes that are unbalanced. We first find the separating plane with a plain SVC and then plot (dashed) the separating hyperplane with automa...scikit-learn.org/stable/auto_examples/svm/plot_separating_hyperplane_unbalanced.html -
SGD: Maximum margin separating hyperplane — sci...
Plot the maximum margin separating hyperplane within a two-class separable dataset using a linear Support Vector Machines classifier trained using SGD. Total running time of the script:(0 minutes 0...scikit-learn.org/stable/auto_examples/linear_model/plot_sgd_separating_hyperplane.html -
11. Common pitfalls and recommended practices —...
The purpose of this chapter is to illustrate some common pitfalls and anti-patterns that occur when using scikit-learn. It provides examples of what not to do, along with a corresponding correct ex...scikit-learn.org/stable/common_pitfalls.html -
14. External Resources, Videos and Talks — scik...
The scikit-learn MOOC: If you are new to scikit-learn, or looking to strengthen your understanding, we highly recommend the scikit-learn MOOC (Massive Open Online Course). The MOOC, created and mai...scikit-learn.org/stable/presentations.html -
2.1. Gaussian mixture models — scikit-learn 1.8...
sklearn.mixture is a package which enables one to learn Gaussian Mixture Models (diagonal, spherical, tied and full covariance matrices supported), sample them, and estimate them from data. Facilit...scikit-learn.org/stable/modules/mixture.html