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Ordinary Least Squares and Ridge Regression ...
1 ] . T y_train = [ 0.5 , 1 ] X_test = np . c_...this_X = 0.1 * np . random . normal ( size = ( 2 , 1 )) + X_train...scikit-learn.org/stable/auto_examples/linear_model/plot_ols_ridge.html -
Gaussian processes on discrete data structures ...
array ([ 1.0 , 1.0 , 2.0 , 2.0 , 3.0 , 3.0 ])...( len ( X_train )), [ 1.0 if c else - 1.0 for c in Y_train ],...scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpr_on_structured_data.html -
Single estimator versus bagging: bias-variance ...
n_estimators - 1 : plt . legend ( loc = ( 1.1 , 0.5 )) plt ....axis = 1 )) ** 2 y_var = np . var ( y_predict , axis = 1 ) print...scikit-learn.org/stable/auto_examples/ensemble/plot_bias_variance.html -
Out-of-core classification of text documents &#...
()[ 1 ], rotation = 30 ) ymax = max ( cls_runtime ) * 1.2 ax...self , encoding = "latin-1" ): HTMLParser . __init__...scikit-learn.org/stable/auto_examples/applications/plot_out_of_core_classification.html -
Detection error tradeoff (DET) curve — sc...
random_state = 1 , n_clusters_per_class = 1 , ) X_train , X_test...n_estimators = 10 , max_features = 1 , random_state = 0 ), "Non-informative...scikit-learn.org/stable/auto_examples/model_selection/plot_det.html -
8.3. Generated datasets — scikit-learn 1....
1.1. Single label # make_blobs creates..."n_informative" : 1 , "n_clusters_per_class" : 1 , "n_classes"...scikit-learn.org/stable/datasets/sample_generators.html -
Kernel Density Estimate of Species Distribution...
subplot ( 1 , 2 , i + 1 ) # construct a kernel density...by Phillips et. al. (2006) [ 1 ] . If available, the example...scikit-learn.org/stable/auto_examples/neighbors/plot_species_kde.html -
Compressive sensing: tomography reconstruction ...
floor_x + 1 )), np . hstack (( 1 - alpha , alpha ))...int ), ( points [ 1 ]) . astype ( int )] = 1 mask = ndimage ....scikit-learn.org/stable/auto_examples/applications/plot_tomography_l1_reconstruction.html -
Hierarchical clustering with and without struct...
) t = 1.5 * np . pi * ( 1 + 3 * np . random . rand ( 1 , n_samples...n_samples , noise = noise ) X1 [:, 1 ] *= 0.5 # Make the roll thinner...scikit-learn.org/stable/auto_examples/cluster/plot_ward_structured_vs_unstructured.html -
L1-based models for Sparse Signals — scik...
1 , n_samples ) y += 0.2 * rng . normal ( 0 , 1 , n_samples...linthresh = 10e-4 , vmin =- 1 , vmax = 1 ), cbar_kws = { "label"...scikit-learn.org/stable/auto_examples/linear_model/plot_lasso_and_elasticnet.html