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Comparison of kernel ridge and Gaussian process...
reshape ( - 1 , 1 ) target = np . sin ( data )...ExpSineSquared(length_scale=1, periodicity=1) Our kernel has two parameters:...scikit-learn.org/stable/auto_examples/gaussian_process/plot_compare_gpr_krr.html -
Tweedie regression on insurance claims — ...
tweedie_powers = [ 1.5 , 1.7 , 1.8 , 1.9 , 1.99 , 1.999 , 1.9999 ] scores_product_model...dev p=1.9990 1.914574e+03 1.914370e+03 1.914537e+03 1.914388e+03...scikit-learn.org/stable/auto_examples/linear_model/plot_tweedie_regression_insurance_claims.html -
Release History — scikit-learn 1.8.0 docu...
Version 1.1.2 Version 1.1.1 Version 1.1.0 Version 1.0 Version 1.0.2...Version 1.2.1 Version 1.2.0 Version 1.1 Version 1.1.3 Version...scikit-learn.org/stable/whats_new.html -
Illustration of Gaussian process classification...
kernels = [ 1.0 * RBF ( length_scale = 1.15 ), 1.0 * DotProduct...)[:, 1 ] Z = Z . reshape ( xx . shape ) plt . subplot ( 1 , 2...scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpc_xor.html -
SVM with custom kernel — scikit-learn 1.8...
T (0 1) """ M = np . array...array ([[ 2 , 0 ], [ 0 , 1.0 ]]) return np . dot ( np . dot (...scikit-learn.org/stable/auto_examples/svm/plot_custom_kernel.html -
3.4. Metrics and scoring: quantifying the quali...
1 , 1 , 1 , 1 , 1 ] >>> y_pred = [ 0 , 1 , 0 ,..., 0 , 1 , 1 , 1 , 1 , 1 ] >>> y_pred = [ 0 , 1 , 0 ,...scikit-learn.org/stable/modules/model_evaluation.html -
Illustration of prior and posterior Gaussian pr...
) axs [ 1 ] . legend ( bbox_to_anchor = ( 1.05 , 1.5 ), loc... ) axs [ 1 ] . legend ( bbox_to_anchor = ( 1.05 , 1.5 ), loc...scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpr_prior_posterior.html -
Feature importances with a forest of trees R...
[{0: 1, 1: 1}, {0: 1, 1: 5}, {0: 1, 1: 1}, {0: 1, 1: 1}] instead...[{0: 1, 1: 1}, {0: 1, 1: 5}, {0: 1, 1: 1}, {0: 1, 1: 1}] instead...scikit-learn.org/stable/auto_examples/ensemble/plot_forest_importances.html -
Demo of HDBSCAN clustering algorithm — sc...
centers = [[ 1 , 1 ], [ - 1 , - 1 ], [ 1.5 , - 1.5 ]] X , labels_true...== - 1 : # Black used for noise. col = [ 0 , 0 , 0 , 1 ] class_index...scikit-learn.org/stable/auto_examples/cluster/plot_hdbscan.html -
Comparing Random Forests and Histogram Gradient...
row = 1 , col = 1 ) fig . add_trace ( line_trace , row = 1 , col...row = 1 , col = 2 ) fig . add_trace ( line_trace , row = 1 , col...scikit-learn.org/stable/auto_examples/ensemble/plot_forest_hist_grad_boosting_comparison.html