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Illustration of prior and posterior Gaussian pr...
This example illustrates the prior and posterior of a GaussianProcessRegressor with different kernels. Mean, standard deviation, and 5 samples are shown for both prior and posterior distributions. ...scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpr_prior_posterior.html -
Compressive sensing: tomography reconstruction ...
This example shows the reconstruction of an image from a set of parallel projections, acquired along different angles. Such a dataset is acquired in computed tomography(CT). Without any prior infor...scikit-learn.org/stable/auto_examples/applications/plot_tomography_l1_reconstruction.html -
Recognizing hand-written digits — scikit-learn ...
This example shows how scikit-learn can be used to recognize images of hand-written digits, from 0-9. Digits dataset: The digits dataset consists of 8x8 pixel images of digits. The images attribute...scikit-learn.org/stable/auto_examples/classification/plot_digits_classification.html -
Demo of HDBSCAN clustering algorithm — scikit-l...
In this demo we will take a look at cluster.HDBSCAN from the perspective of generalizing the cluster.DBSCAN algorithm. We’ll compare both algorithms on specific datasets. Finally we’ll evaluate HDB...scikit-learn.org/stable/auto_examples/cluster/plot_hdbscan.html -
Sparse coding with a precomputed dictionary — s...
Transform a signal as a sparse combination of Ricker wavelets. This example visually compares different sparse coding methods using the SparseCoder estimator. The Ricker (also known as Mexican hat ...scikit-learn.org/stable/auto_examples/decomposition/plot_sparse_coding.html -
Density Estimation for a Gaussian mixture — sci...
Plot the density estimation of a mixture of two Gaussians. Data is generated from two Gaussians with different centers and covariance matrices. Total running time of the script:(0 minutes 0.121 sec...scikit-learn.org/stable/auto_examples/mixture/plot_gmm_pdf.html -
Lasso on dense and sparse data — scikit-learn 1...
We show that linear_model.Lasso provides the same results for dense and sparse data and that in the case of sparse data the speed is improved. Comparing the two Lasso implementations on Dense data:...scikit-learn.org/stable/auto_examples/linear_model/plot_lasso_dense_vs_sparse_data.html -
Map data to a normal distribution — scikit-lear...
This example demonstrates the use of the Box-Cox and Yeo-Johnson transforms through PowerTransformer to map data from various distributions to a normal distribution. The power transform is useful a...scikit-learn.org/stable/auto_examples/preprocessing/plot_map_data_to_normal.html -
Neighborhood Components Analysis Illustration —...
This example illustrates a learned distance metric that maximizes the nearest neighbors classification accuracy. It provides a visual representation of this metric compared to the original point sp...scikit-learn.org/stable/auto_examples/neighbors/plot_nca_illustration.html -
2.6. Covariance estimation — scikit-learn 1.8.0...
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