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single_source_shortest_path_length — scik...
2: 2} >>> graph = np . ones...h ( graph , 2 ) . items ()) [(0, 1), (1, 1), (2, 0), (3, 1),...scikit-learn.org/stable/modules/generated/sklearn.utils.graph.single_source_shortest_path_length.... -
Lasso — scikit-learn 1.8.0 documentation
[ 2 , 2 ]], [ 0 , 1 , 2 ]) Lasso(alpha=0.1)...\(||y||_2^2 / n_{\text{samples}}\) . The target can be a 2-dimensional...scikit-learn.org/stable/modules/generated/sklearn.linear_model.Lasso.html -
kNN search in Elasticsearch | Elastic Docs
- 1) cosine : (2 * _score) - 1 dot_product : (2 * _score) - 1..."k": 2, "num_candidates": 2, "inner_hits":...www.elastic.co/docs/solutions/search/vector/knn -
Outlier detection with Local Outlier Factor (LO...
2 ) X_inliers = np . r_ [ X_inliers + 2 , X_inliers...relative to this cluster, and 2) smaller than the maximum number...scikit-learn.org/stable/auto_examples/neighbors/plot_lof_outlier_detection.html -
dcg_score — scikit-learn 1.8.0 documentation
log_base = 2 , sample_weight = None , ignore_ties...outputs. log_base float, default=2 Base of the logarithm used for...scikit-learn.org/stable/modules/generated/sklearn.metrics.dcg_score.html -
PoissonRegressor — scikit-learn 1.8.0 doc...
determination R^2. R^2 uses squared error and D^2 uses the deviance...() >>> X = [[ 1 , 2 ], [ 2 , 3 ], [ 3 , 4 ], [ 4 , 3...scikit-learn.org/stable/modules/generated/sklearn.linear_model.PoissonRegressor.html -
v_measure_score — scikit-learn 1.8.0 docu...
2 ], [ 0 , 0 , 1 , 1 ])) 0.8 >>>...% v_measure_score ([ 0 , 1 , 2 , 3 ], [ 0 , 0 , 1 , 1 ])) 0.67...scikit-learn.org/stable/modules/generated/sklearn.metrics.v_measure_score.html -
kneighbors_graph — scikit-learn 1.8.0 doc...
p = 2 , metric_params = None , include_self...standard Euclidean distance when p = 2. See the documentation of scipy.spatial.distance...scikit-learn.org/stable/modules/generated/sklearn.neighbors.kneighbors_graph.html -
dict_learning_online — scikit-learn 1.8.0...
X_hat - X ) ** 2 , axis = 1 ) / np . sum ( X ** 2 , axis = 1 ))...dict_learning_online ( X , n_components = 2 , * , alpha = 1 , max_iter = 100...scikit-learn.org/stable/modules/generated/sklearn.decomposition.dict_learning_online.html -
confusion_matrix — scikit-learn 1.8.0 doc...
>>> y_true = [ 2 , 0 , 2 , 2 , 0 , 1 ] >>> y_pred...y_pred = [ 0 , 0 , 2 , 2 , 0 , 2 ] >>> confusion_matrix...scikit-learn.org/stable/modules/generated/sklearn.metrics.confusion_matrix.html