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Bunch — scikit-learn 1.7.0 documentation
import Bunch >>> b = Bunch ( a = 1 , b = 2 ) >>> b [ 'b' ] 2...b 2 >>> b . a = 3 >>> b [ 'a' ] 3 >>> b . c = 6 >>> b [ 'c' ]...scikit-learn.org/stable/modules/generated/sklearn.utils.Bunch.html -
favicon_16x16.png
35285816 width=16, height=16, bitDepth=8, colorType=RGBAlpha, c...compressionMethod=deflate, filterMethod=adaptive, interlaceMethod=none RGB...www.elastic.co/favicon_16x16.png -
favicon-96x96.png
35285816 width=96, height=96, bitDepth=8, colorType=RGBAlpha, c...compressionMethod=deflate, filterMethod=adaptive, interlaceMethod=none RGB...www.elastic.co/favicon-96x96.png -
apple-icon-144x144.png
35285816 width=144, height=144, bitDepth=8, colorType=RGBAlpha, ...compressionMethod=deflate, filterMethod=adaptive, interlaceMethod=none RGB...www.elastic.co/apple-icon-144x144.png -
Recursive feature elimination — scikit-learn 1....
ha = "center" , va = "center" , color = "black" ) plt...digits dataset digits = load_digits () X = digits . images . reshape...scikit-learn.org/stable/auto_examples/feature_selection/plot_rfe_digits.html -
plot_hgbt_regression.zip
py """ ========== Features in Histogram Gradient...Gradient Boosting Trees ========== :ref:`histogram_based_gradient_boosting`...scikit-learn.org/stable/_downloads/ef504a3cb245a55fde178198c8218b4a/plot_hgbt_regression.zip -
Process data from Elastic integrations with the...
data_stream = > true ssl = > true ecs_compatibility = > v8 } # For...api_key = > "yourapikey - here" data_stream = > true ssl = > true...www.elastic.co/observability-labs/blog/logstash-integration-filter-plugin -
plot_classifier_comparison.rst.txt
py: ========== Classifier comparison ========== A comparison...random_state=42), SVC(gamma=2, C=1, random_state=42), GaussianProcessClass(1.0...scikit-learn.org/stable/_sources/auto_examples/classification/plot_classifier_comparison.rst.txt -
make_swiss_roll — scikit-learn 1.7.0 documentation
n_samples = 100 , * , noise = 0.0 , random_state = None , hole = False...X , t = make_swiss_roll ( noise = 0.05 , random_state = 0 ) >>>...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_swiss_roll.html -
LinearRegression — scikit-learn 1.7.0 documenta...
fit_intercept = True , copy_X = True , tol = 1e-06 , n_jobs = None ,...3 ]]) >>> # y = 1 * x_0 + 2 * x_1 + 3 >>> y = np . dot ( X ,...scikit-learn.org/stable/modules/generated/sklearn.linear_model.LinearRegression.html
