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12.1. Array API support (experimental) — scikit...
2.2. Meta-estimators # Meta-estimators...X_trans . device . type 'cuda' 12.1.2. Support for Array API -compatible...scikit-learn.org/stable/modules/array_api.html -
Examples based on real world datasets — scikit-...
Applications to real world problems with some medium sized datasets or interactive user interface. Compressive sensing: tomography reconstruction with L1 prior (Lasso) Faces recognition example usi...scikit-learn.org/stable/auto_examples/applications/index.html -
sklearn.kernel_approximation — scikit-learn 1.7...
Approximate kernel feature maps based on Fourier transforms and count sketches. User guide. See the Kernel Approximation section for further details.scikit-learn.org/stable/api/sklearn.kernel_approximation.html -
sklearn.random_projection — scikit-learn 1.7.2 ...
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 -
fetch_species_distributions — scikit-learn 1.7....
Gallery examples: Species distribution modeling Kernel Density Estimate of Species Distributionsscikit-learn.org/stable/modules/generated/sklearn.datasets.fetch_species_distributions.html -
load_sample_image — scikit-learn 1.7.2 document...
Skip to main content Back to top Ctrl + K GitHub Choose version load_sample_image # sklearn.datasets. load_sample_ima...scikit-learn.org/stable/modules/generated/sklearn.datasets.load_sample_image.html -
sklearn.naive_bayes — scikit-learn 1.7.2 docume...
Naive Bayes algorithms. These are supervised learning methods based on applying Bayes’ theorem with strong (naive) feature independence assumptions. User guide. See the Naive Bayes section for furt...scikit-learn.org/stable/api/sklearn.naive_bayes.html -
estimator_checks_generator — scikit-learn 1.7.2...
Skip to main content Back to top Ctrl + K GitHub Choose version estimator_checks_generator # sklearn.utils.estimator_...scikit-learn.org/stable/modules/generated/sklearn.utils.estimator_checks.estimator_checks_generat... -
fetch_20newsgroups_vectorized — scikit-learn 1....
Gallery examples: Model Complexity Influence Multiclass sparse logistic regression on 20newgroups The Johnson-Lindenstrauss bound for embedding with random projectionsscikit-learn.org/stable/modules/generated/sklearn.datasets.fetch_20newsgroups_vectorized.html -
fetch_california_housing — scikit-learn 1.7.2 d...
Gallery examples: Comparing Random Forests and Histogram Gradient Boosting models Early stopping in Gradient Boosting Imputing missing values with variants of IterativeImputer Imputing missing valu...scikit-learn.org/stable/modules/generated/sklearn.datasets.fetch_california_housing.html