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SVM-Anova: SVM with univariate feature selectio...
2 * rng . random (( X . shape [...scikit-learn.org/stable/auto_examples/svm/plot_svm_anova.html -
Gaussian process classification (GPC) on iris d...
: 2 ] # we only take the first two...m_max]x[y_min, y_max]. plt . subplot ( 1 , 2 , i + 1 ) Z = clf . predict_proba...scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpc_iris.html -
Comparing random forests and the multi-output m...
random_state = 2 ) regr_rf . fit ( X_train , y_train..."target 1" ) plt . ylabel ( "target 2" ) plt . title ( "Comparing random...scikit-learn.org/stable/auto_examples/ensemble/plot_random_forest_regression_multioutput.html -
7.8. Pairwise metrics, Affinities and Kernels —...
for all a and b 2. d ( a , b ) == 0 , if and only...pairwise_kernels >>> X = np . array ([[ 2 , 3 ], [ 3 , 5 ], [ 5 , 8 ]])...scikit-learn.org/stable/modules/metrics.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 -
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... -
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 -
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 -
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_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