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sklearn.mixture — scikit-learn 1.8.0 docu...
Mixture modeling algorithms. User guide. See the Gaussian mixture models section for further details.scikit-learn.org/stable/api/sklearn.mixture.html -
sklearn.random_projection — scikit-learn ...
Random projection transformers. Random projections are a simple and computationally efficient way to reduce the dimensionality of the data by trading a controlled amount of accuracy (as additional ...scikit-learn.org/stable/api/sklearn.random_projection.html -
12.1. Array API support (experimental) — ...
refer to SciPy’s Array API documentation . Some scikit-learn estimators...affect the rest of the documentation. Scikit-learn accepts array-like...scikit-learn.org/stable/modules/array_api.html -
1.5. Stochastic Gradient Descent — scikit...
Examples Classification of text documents using sparse features 1.5.5....scikit-learn.org/stable/modules/sgd.html -
Release Highlights for scikit-learn 1.5 —...
We are pleased to announce the release of scikit-learn 1.5! Many bug fixes and improvements were added, as well as some key new features. Below we detail the highlights of this release. For an exha...scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_5_0.html -
Release Highlights for scikit-learn 0.22 —...
We are pleased to announce the release of scikit-learn 0.22, which comes with many bug fixes and new features! We detail below a few of the major features of this release. For an exhaustive list of...scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_0_22_0.html -
Comparing different clustering algorithms on to...
This example shows characteristics of different clustering algorithms on datasets that are “interesting” but still in 2D. With the exception of the last dataset, the parameters of each of these dat...scikit-learn.org/stable/auto_examples/cluster/plot_cluster_comparison.html -
Various Agglomerative Clustering on a 2D embedd...
An illustration of various linkage option for agglomerative clustering on a 2D embedding of the digits dataset. The goal of this example is to show intuitively how the metrics behave, and not to fi...scikit-learn.org/stable/auto_examples/cluster/plot_digits_linkage.html -
Plot classification boundaries with different S...
This example shows how different kernels in a SVC(Support Vector Classifier) influence the classification boundaries in a binary, two-dimensional classification problem. SVCs aim to find a hyperpla...scikit-learn.org/stable/auto_examples/svm/plot_svm_kernels.html -
5. Inspection — scikit-learn 1.8.0 docume...
Predictive performance is often the main goal of developing machine learning models. Yet summarizing performance with an evaluation metric is often insufficient: it assumes that the evaluation metr...scikit-learn.org/stable/inspection.html