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Ledoit-Wolf vs OAS estimation — scikit-learn 1....
subplot ( 2 , 1 , 2 ) plt . errorbar ( n_samples_range...shrinkage_ # plot MSE plt . subplot ( 2 , 1 , 1 ) plt . errorbar ( n_samples_range...scikit-learn.org/stable/auto_examples/covariance/plot_lw_vs_oas.html -
LassoLarsIC — scikit-learn 1.8.0 documentation
[[ - 2 , 2 ], [ - 1 , 1 ], [ 0 , 0 ], [ 1 , 1 ], [ 2 , 2 ]] >>>...>>> y = [ - 2.2222 , - 1.1111 , 0 , - 1.1111 , - 2.2222 ] >>>...scikit-learn.org/stable/modules/generated/sklearn.linear_model.LassoLarsIC.html -
Theil-Sen Regression — scikit-learn 1.8.0 docum...
Linear model y = 3*x + N(2, 0.1**2) x = np . random . randn (...Linear model y = 3*x + N(2, 0.1**2) x = np . random . randn (...scikit-learn.org/stable/auto_examples/linear_model/plot_theilsen.html -
mean_tweedie_deviance — scikit-learn 1.8.0 docu...
y_true = [ 2 , 0 , 1 , 4 ] >>> y_pred = [ 0.5 , 0.5 , 2. , 2. ] >>>...>= 0 and y_pred > 0. 1 < p < 2 : Compound Poisson distribution....scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_tweedie_deviance.html -
DistanceMetric — scikit-learn 1.8.0 documentation
HaversineDistance 2 arcsin(sqrt(sin^2(0.5*dx) + cos(x1)cos(x2)sin^2(0.5*dy)))...'euclidean' ) >>> X = [[ 1 , 2 ], [ 3 , 4 ], [ 5 , 6 ]] >>> Y...scikit-learn.org/stable/modules/generated/sklearn.metrics.DistanceMetric.html -
zero_one_loss — scikit-learn 1.8.0 documentation
2 , 3 , 4 ] >>> y_true = [ 2 , 2 , 3 , 4 ] >>>...], [ 1 , 1 ]]), np . ones (( 2 , 2 ))) 0.5 On this page This Page...scikit-learn.org/stable/modules/generated/sklearn.metrics.zero_one_loss.html -
auto_examples_python.zip
- l / 2.0) ** 2 + (y - l / 2.0) ** 2 < (l / 2.0) ** 2 mask =...+ 1, figsize=(4 * 2.2, n_classifiers * 2.2), ) evaluation_results...scikit-learn.org/stable/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip -
plot_classifier_comparison.zip
make_classification( n_features=2, n_redundant=0, n_informative=2, random_state=1,...rng = np.random.RandomState(2) X += 2 * rng.uniform(size=X.shape)...scikit-learn.org/stable/_downloads/ce35bcc69acbd491cf7ac77fa17889d5/plot_classifier_comparison.zip -
Comparing different hierarchical linkage method...
xlim ( - 2.5 , 2.5 ) plt . ylim ( - 2.5 , 2.5 ) plt . xticks..."n_clusters" : 2 }), ( noisy_moons , { "n_clusters" : 2 }), ( varied...scikit-learn.org/stable/auto_examples/cluster/plot_linkage_comparison.html -
roc_curve — scikit-learn 1.8.0 documentation
2 , 2 ]) >>> scores = np . array ([...Returns : fpr ndarray of shape (>2,) Increasing false positive rates...scikit-learn.org/stable/modules/generated/sklearn.metrics.roc_curve.html