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GMM Initialization Methods — scikit-learn 1.8.0...
1 ], s = 75 , marker = "D" , c = "orange" , lw = 1.5 , edgecolors...random_state = 0 ) X = X [:, :: - 1 ] n_samples = 4000 n_components...scikit-learn.org/stable/auto_examples/mixture/plot_gmm_init.html -
Univariate Feature Selection — scikit-learn 1.8...
shape [ - 1 ]) plt . figure ( 1 ) plt . clf () plt ....RandomState ( 42 ) . uniform ( 0 , 0.1 , size = ( X . shape [ 0 ], 20...scikit-learn.org/stable/auto_examples/feature_selection/plot_feature_selection.html -
SVM Tie Breaking Example — scikit-learn 1.8.0 d...
1 ] . min (), X [:, 1 ] . max ()] xs = np...xlim [ 1 ], 1000 ) ys = np . linspace ( ylim [ 0 ], ylim [ 1 ], 1000...scikit-learn.org/stable/auto_examples/svm/plot_svm_tie_breaking.html -
Recursive feature elimination — scikit-learn 1....
n_features_to_select = 1 , step = 1 )), ] ) pipe . fit ( X ,...(( len ( digits . images ), - 1 )) y = digits . target pipe =...scikit-learn.org/stable/auto_examples/feature_selection/plot_rfe_digits.html -
Understanding the decision tree structure — sci...
[{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/tree/plot_unveil_tree_structure.html -
API Reference — scikit-learn 1.8.0 documentation
Scale each feature to the [-1, 1] range without breaking the...(Kluger, 2003) [R2af9f5762274-1] . sklearn.cluster SpectralClustering...scikit-learn.org/stable/api/index.html -
Visualizing the probabilistic predictions of a ...
uniform ( low =- 1 , high = 1 , size = ( n_samples , 2...> 0 , xor [ "Feature #1" ] + noise [:, 1 ] > 0 ) X = xor [ feature_names...scikit-learn.org/stable/auto_examples/ensemble/plot_voting_decision_regions.html -
Frequently Asked Questions — scikit-learn 1.8.0...
reshape ( - 1 , 1 ) >>> X array([[0], [1], [2]]) >>> # We...'brute' ) (array([0, 1]), array([ 0, 0, -1])) Note that the example...scikit-learn.org/stable/faq.html -
Importance of Feature Scaling — scikit-learn 1....
it has a standard deviation of 1 and a mean of 0. Even if tree...variable “hue” varies between 1 and 10. Because of this, distances...scikit-learn.org/stable/auto_examples/preprocessing/plot_scaling_importance.html -
Agglomerative clustering with different metrics...
1 , 1 ]) for l , color , n in zip...figure () plt . axes ([ 0 , 0 , 1 , 1 ]) for l , color in zip ( np...scikit-learn.org/stable/auto_examples/cluster/plot_agglomerative_clustering_metrics.html