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sklearn.datasets — scikit-learn 1.8.0 doc...
Generate the "Friedman #1" regression problem. make_friedman2...scikit-learn.org/stable/api/sklearn.datasets.html -
Combine predictors using stacking — sciki...
versionadded:: 1.1 The 'prefit' option was added in 1.1 .. note::...versionchanged:: 1.1 Added option 'quantile'. .. versionchanged:: 1.3 Added...scikit-learn.org/stable/auto_examples/ensemble/plot_stack_predictors.html -
Frequently Asked Questions — scikit-learn...
reshape ( - 1 , 1 ) >>> X array([[0], [1], [2]]) >>>...'brute' ) (array([0, 1]), array([ 0, 0, -1])) Note that the example...scikit-learn.org/stable/faq.html -
Label Propagation digits: Active learning ̵...
support 0 1.00 1.00 1.00 22 1 0.85 1.00 0.92 22 2 1.00 1.00 1.00 28...support 0 1.00 1.00 1.00 22 1 0.85 1.00 0.92 22 2 1.00 1.00 1.00 27...scikit-learn.org/stable/auto_examples/semi_supervised/plot_label_propagation_digits_active_learni... -
Demo of affinity propagation clustering algorit...
centers = [[ 1 , 1 ], [ - 1 , - 1 ], [ 1 , - 1 ]] X , labels_true...0 ]], [ cluster_center [ 1 ], x [ 1 ]], color = col [ "color"...scikit-learn.org/stable/auto_examples/cluster/plot_affinity_propagation.html -
Probability Calibration for 3-class classificat...
[{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/calibration/plot_calibration_multiclass.html -
LogFormatUtils (Spring Framework 7.0.1 API)
1 Author: Rossen Stoyanchev, Juergen...after which to truncate, or -1 for unlimited replaceNewlinesAndCo...docs.spring.io/spring-framework/docs/current/javadoc-api/org/springframework/core/log/LogFormatUt... -
Simple 1D Kernel Density Estimation — sci...
1 , int ( 0.3 * N )), np . random . normal ( 5 , 1 , int...score_samples ( X_plot ) ax [ 1 , 1 ] . fill ( X_plot [:, 0 ], np...scikit-learn.org/stable/auto_examples/neighbors/plot_kde_1d.html -
Lagged features for time series forecasting ...
1 ± 1.1" "19.9 ± 1.6" "22.7 ± 3.1"..."17.1 ± 1.1" "19.9 ± 1.6" "22.7 ± 3.1"...scikit-learn.org/stable/auto_examples/applications/plot_time_series_lagged_features.html -
1.11. Ensembles: Gradient boosting, random fore...
Gradient Boosting models 1.11.1.1.1. Usage # Most of the parameters...= [[ 1 , 0 ], ... [ 1 , 0 ], ... [ 1 , 0 ], ... [ 0 , 1 ]] >>>...scikit-learn.org/stable/modules/ensemble.html