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sitemap-index
cnews/sitemap-2025-10-article.xml2025-10-31T23:55:58Zhttps:/...bcnews/sitemap-2025-10-video.xml2025-10-31T23:55:52Zhttps://...www.nbcnews.com/sitemap/nbcnews/sitemap-index -
Incorporating static relevance signals into the...
score = bm25_score + pagerank / (10 + pagerank) . With the script_score...saturation(doc['pagerank'].value, 10)" } } } } pagerank must be mapped...www.elastic.co/docs/solutions/search/full-text/search-relevance/static-scoring-signals -
Search API and templates | Elastic Docs
"boost": 10}, {"name": "description", "boost":..."explain": false, "from": 0, "size": 10 } } } } A search query using...www.elastic.co/docs/solutions/search/search-applications/search-application-api -
reconstruct_from_patches_2d — scikit-learn 1.7....
patch_size = ( 10 , 10 )) >>> print ( 'Patches shape:...)) Patches shape: (263758, 10, 10, 3) >>> image_reconstructed...scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.image.reconstruct_from_patch... -
grid_search.rst.txt
10, 100, 1000], 'kernel': ['linear']}, {'C': [1, 10, 100,...{'max_depth': [3, 5, 10], ... 'min_samples_split': [2, 5, 10]} >>> base_estimator...scikit-learn.org/stable/_sources/modules/grid_search.rst.txt -
Using Cohere with Elasticsearch | Elastic Docs
the first 10 results for document in raw_documents[0:10]: print(f'Title:...the top 10 results for document in ranked_documents[0:10]: print(f"Title:...www.elastic.co/docs/solutions/search/semantic-search/cohere-es -
make_blobs — scikit-learn 1.7.2 documentation
center_box = (-10.0, 10.0) , shuffle = True , random_state...float (min, max), default=(-10.0, 10.0) The bounding box for each...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_blobs.html -
Search templates | Elastic Docs
"size": 10 } } When rendered, the template...world" } }, "from": "20", "size": "10" } } You can also use the API...www.elastic.co/docs/solutions/search/search-templates -
kmeans_plusplus — scikit-learn 1.7.2 documentation
[ 10 , 2 ], [ 10 , 4 ], [ 10 , 0 ]]) >>> centers...random_state = 0 ) >>> centers array([[10, 2], [ 1, 0]]) >>> indices array([3,...scikit-learn.org/stable/modules/generated/sklearn.cluster.kmeans_plusplus.html -
plot_discretization_strategies.py
n_samples // 10, n_samples * 4 // 10, n_samples // 10, n_samples...n_samples * 4 // 10, ], cluster_std=0.5, centers=centers_0, random_state=random_state,...scikit-learn.org/stable/_downloads/43e84df0b93ff974da370e8da900f2ee/plot_discretization_strategie...