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lasso_path — scikit-learn 1.7.1 documentation
precompute = 'auto' , Xy = None , copy_X = True , coef_init = None...y , * , eps = 0.001 , n_alphas = 100 , alphas = None , precompute...scikit-learn.org/stable/modules/generated/sklearn.linear_model.lasso_path.html -
neighbors.rst.txt
_neighbors: ========== Nearest Neighbors ========== .. sectionauthor::...Unsupervised Nearest Neighbors ========== :class:`NearestNeighbors`...scikit-learn.org/stable/_sources/modules/neighbors.rst.txt -
Regularization path of L1- Logistic Regression ...
classification X = X [ y != 2 ] y = y [ y != 2 ] Compute regularization...datasets iris = datasets . load_iris () X = iris . data y = iris . target...scikit-learn.org/stable/auto_examples/linear_model/plot_logistic_path.html -
KernelDensity — scikit-learn 1.7.1 documentation
metric = 'euclidean' , atol = 0 , rtol = 0 , breadth_first = True..., bandwidth = 1.0 , algorithm = 'auto' , kernel = 'gaussian' ,...scikit-learn.org/stable/modules/generated/sklearn.neighbors.KernelDensity.html -
SpectralEmbedding — scikit-learn 1.7.1 document...
n_components = 2 , * , affinity = 'nearest_neighbors' , gamma = None...random_state = None , eigen_solver = None , eigen_tol = 'auto' ,...scikit-learn.org/stable/modules/generated/sklearn.manifold.SpectralEmbedding.html -
Incremental PCA — scikit-learn 1.7.1 documentation
X_transformed [ y == i , 0 ], X_transformed [ y == i , 1 ], color = color...IncrementalPCA iris = load_iris () X = iris . data y = iris . target...scikit-learn.org/stable/auto_examples/decomposition/plot_incremental_pca.html -
Joint feature selection with multi-task Lasso —...
n_tasks = 100 , 30 , 40 n_relevant_features = 5 coef = np . zeros...feature_to_plot ], color = "seagreen" , linewidth = lw , label = "Ground truth"...scikit-learn.org/stable/auto_examples/linear_model/plot_multi_task_lasso_support.html -
validation_curve — scikit-learn 1.7.1 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 -
recall_score — scikit-learn 1.7.1 documentation
labels = None , pos_label = 1 , average = 'binary' , sample_weight...sample_weight = None , zero_division = 'warn' ) [source] # Compute...scikit-learn.org/stable/modules/generated/sklearn.metrics.recall_score.html -
ExtraTreeRegressor — scikit-learn 1.7.1 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