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make_sparse_spd_matrix — scikit-learn 1.7.0 doc...
make_sparse_spd_matrix ( n_dim = 1 , * , alpha = 0.95 , norm_diag = False , smallest_coef...smallest_coef = 0.1 , largest_coef = 0.9 , sparse_format = None , random_state...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_sparse_spd_matrix.html -
validation_curve — scikit-learn 1.7.0 documenta...
groups = None , cv = None , scoring = None , n_jobs = None ,...pre_dispatch = 'all' , verbose = 0 , error_score = nan , fit_params...scikit-learn.org/stable/modules/generated/sklearn.model_selection.validation_curve.html -
GaussianRandomProjection — scikit-learn 1.7.0 d...
GaussianRandomProjec ( n_components = 'auto' , * , eps = 0.1 , compute_inverse_components...compute_inverse_components = False , random_state = None ) [source] # Reduce...scikit-learn.org/stable/modules/generated/sklearn.random_projection.GaussianRandomProjection.html -
brier_score_loss — scikit-learn 1.7.0 documenta...
sample_weight = None , pos_label = None , labels = None , scale_by_half...default=None Label of the positive class when y_proba.shape = (n_samples,)...scikit-learn.org/stable/modules/generated/sklearn.metrics.brier_score_loss.html -
Orthogonal Matching Pursuit — scikit-learn 1.7....
data # y = Xw # |x|_0 = n_nonzero_coefs y , X , w = make_sparse_coded_signal...n_samples = 1 , n_components = n_components , n_features = n_features...scikit-learn.org/stable/auto_examples/linear_model/plot_omp.html -
Early stopping in Gradient Boosting — scikit-le...
params = dict ( n_estimators = 1000 , max_depth = 5 , learning_rate...learning_rate = 0.1 , random_state = 42 ) gbm_full = GradientBoostingRegr...scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_early_stopping.html -
make_blobs — scikit-learn 1.7.0 documentation
( n_samples = 100 , n_features = 2 , * , centers = None , cluster_std...cluster_std = 1.0 , center_box = (-10.0, 10.0) , shuffle = True ,...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_blobs.html -
1.12. Multiclass and multioutput algorithms — s...
n_informative = 30 , n_classes = 3 , ... random_state = 1 ) >>> y2 = shuffle..., y = datasets . load_iris ( return_X_y = True ) >>> clf = OutputCodeClassifier...scikit-learn.org/stable/modules/multiclass.html -
1.8. Cross decomposition — scikit-learn 1.7.0 d...
transformed(X) = XU and transformed(Y) = YV . If n_components == 1 , PLSSVD...\(\Omega = \alpha \Xi\) . Then, we have \(Y = \Omega \Delta^T = \alpha...scikit-learn.org/stable/modules/cross_decomposition.html -
ExtraTreeRegressor — scikit-learn 1.7.0 documen...
criterion = 'squared_error' , splitter = 'random' , max_depth = None...min_weight_fraction_leaf = 0.0 , max_features = 1.0 , random_state = None , m...scikit-learn.org/stable/modules/generated/sklearn.tree.ExtraTreeRegressor.html