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fetch_rcv1 — scikit-learn 1.5.2 documentation
Added in version 1.5. delay float, default=1.0 Number of seconds...False , n_retries = 3 , delay = 1.0 ) [source] # Load the RCV1 multilabel...scikit-learn.org/stable/modules/generated/sklearn.datasets.fetch_rcv1.html -
Orthogonal Matching Pursuit — scikit-learn 1.5....
1 , 1 ) plt . xlim ( 0 , 512 ) plt...make_sparse_coded_signal ( n_samples = 1 , n_components = n_components...scikit-learn.org/stable/auto_examples/linear_model/plot_omp.html -
load_wine — scikit-learn 1.5.2 documentation
1, 2]) >>> list ( data . target_names...[np.str_('class_0'), np.str_('class_1'), np.str_('class_2')] Gallery...scikit-learn.org/stable/modules/generated/sklearn.datasets.load_wine.html -
ledoit_wolf — scikit-learn 1.5.2 documentation
regularized (shrunk) covariance is: (1 - shrinkage) * cov + shrinkage...scikit-learn.org/stable/modules/generated/sklearn.covariance.ledoit_wolf.html -
Caching nearest neighbors — scikit-learn 1.5.2 ...
= True ) n_neighbors_list = [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 ,...fig , axes = plt . subplots ( 1 , 2 , figsize = ( 8 , 4 )) axes...scikit-learn.org/stable/auto_examples/neighbors/plot_caching_nearest_neighbors.html -
Support — scikit-learn 1.5.2 documentation
Resources # This documentation is for 1.5.2. Find documentation for other...scikit-learn.org/stable/support.html -
Ledoit-Wolf vs OAS estimation — scikit-learn 1....
covariance matrix (AR(1) process) r = 0.1 real_cov = toeplitz (...plot MSE plt . subplot ( 2 , 1 , 1 ) plt . errorbar ( n_samples_range...scikit-learn.org/stable/auto_examples/covariance/plot_lw_vs_oas.html -
Effect of varying threshold for self-training —...
mean ( axis = 1 ), yerr = scores . std ( axis = 1 ), capsize =...( axis = 1 ), yerr = amount_labeled . std ( axis = 1 ), capsize...scikit-learn.org/stable/auto_examples/semi_supervised/plot_self_training_varying_threshold.html -
A demo of the mean-shift clustering algorithm —...
centers = [[ 1 , 1 ], [ - 1 , - 1 ], [ 1 , - 1 ]] X , _ = make_blobs...matplotlib.pyplot as plt plt . figure ( 1 ) plt . clf () colors = [ "#dede00"...scikit-learn.org/stable/auto_examples/cluster/plot_mean_shift.html -
PCA example with Iris Data-set — scikit-learn 1...
1 ] . mean () + 1.5 , X [ y == label , 2...features 1 and 2 Sparsity Example: Fitting only features 1 and 2...scikit-learn.org/stable/auto_examples/decomposition/plot_pca_iris.html