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inplace_csr_row_normalize_l1 — scikit-learn 1.7...
2 , 3 , 4 ]) >>> indices = np . array ([ 0 , 1 , 2 , 3 ])...>>> data = np . array ([ 1.0 , 2.0 , 3.0 , 4.0 ]) >>> X = csr_matrix...scikit-learn.org/stable/modules/generated/sklearn.utils.sparsefuncs_fast.inplace_csr_row_normaliz... -
label_ranking_average_precision_score — scikit-...
2 , 0.1 ]]) >>> label_ranking_a...scikit-learn.org/stable/modules/generated/sklearn.metrics.label_ranking_average_precision_score.html -
dcg_score — scikit-learn 1.7.2 documentation
log_base = 2 , sample_weight = None , ignore_ties...outputs. log_base float, default=2 Base of the logarithm used for...scikit-learn.org/stable/modules/generated/sklearn.metrics.dcg_score.html -
make_friedman1 — scikit-learn 1.7.2 documentation
2 ] - 0.5 ) ** 2 + 10 * X [:, 3 ] + 5 *...in Friedman [1] and Breiman [2]. Inputs X are independent features...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_friedman1.html -
Illustration of Gaussian process classification...
2 ) Y = np . logical_xor ( X [:,...DotProduct ( sigma_0 = 1.0 ) ** 2 ] for i , kernel in enumerate...scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpc_xor.html -
all_estimators — scikit-learn 1.7.2 documentation
<class 'tuple'> >>> estimators [: 2 ] [('ARDRegression', <class '..."classifier" ) >>> classifiers [: 2 ] [('AdaBoostClassifier', <class...scikit-learn.org/stable/modules/generated/sklearn.utils.discovery.all_estimators.html -
Gradient Boosting regression — scikit-learn 1.7...
2 , 2 ) # `labels` argument in boxplot...permutation methods identify the same 2 strongly predictive features but...scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_regression.html -
power_transform — scikit-learn 1.7.2 documentation
2 ], [ 3 , 2 ], [ 4 , 5 ]] >>> print...and negative values ‘box-cox’ [2] , only works with strictly positive...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.power_transform.html -
t-SNE: The effect of various perplexity values ...
n_samples = 150 n_components = 2 ( fig , subplots ) = plt . subplots.... scatter ( X [:, 0 ], X [:, 2 ], c = color ) ax . xaxis . set_major_formatter...scikit-learn.org/stable/auto_examples/manifold/plot_t_sne_perplexity.html -
Importance of Feature Scaling — scikit-learn 1....
section we select a subset of 2 features that have values with...) = plt . subplots ( ncols = 2 , figsize = ( 12 , 6 )) fit_and_plot_model...scikit-learn.org/stable/auto_examples/preprocessing/plot_scaling_importance.html