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1.1. Linear Models — scikit-learn 1.7.2 documen...
a cost of \(O(n_{\text{samples}} n_{\text{features}}^2)\) , assuming...assuming that \(n_{\text{samples}} \geq n_{\text{features}}\) . 1.1.2....scikit-learn.org/stable/modules/linear_model.html -
kNN search in Elasticsearch | Elastic Docs
sibling nested fields in nested KNN search Stack 9.2.0 Nested knn..."type": "nested", "properties": { "text": { "type": "text" }, "vector":...www.elastic.co/docs/solutions/search/vector/knn -
webpack-790dbff81ecb3dfd.js
test(e))d[e]=0;else{var n=new Pr...n.tokenBinary",67234:"icon.nested",67929:"icon.editor_headin...www.elastic.co/_next/static/chunks/webpack-790dbff81ecb3dfd.js -
Elasticsearch index engines | App Search docume...
keyword text constant_keyword text wildcard text text text geo_point..."manager.name.first": "text", "manager.name.last": "text" } Nested fields filters...www.elastic.co/guide/en/app-search/current/elasticsearch-engines.html -
SpectralBiclustering — scikit-learn 1.7.2 docum...
n_best int, default=3 Number of best singular vectors...'bistochastic' , n_components = 6 , n_best = 3 , svd_method = 'randomized'...scikit-learn.org/stable/modules/generated/sklearn.cluster.SpectralBiclustering.html -
CountVectorizer — scikit-learn 1.7.2 documentation
on a Text Dataset Semi-supervised Classification on a Text Dataset...class sklearn.feature_extraction.text. CountVectorizer ( * , input='content'...scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.text.CountVectorizer.html -
Elastic APM events intake API | Elastic Docs
"ab_testing":true,"segment":5}}} {"err..."description": "Origin contains the self-nested field groups for cloud.", "type":...www.elastic.co/docs/solutions/observability/apm/elastic-apm-events-intake-api -
linear_model.rst.txt
cost of :math:`O(n_{\text{samples}} n_{\text{features}}^2)`, assuming...that :math:`n_{\text{samples}} \geq n_{\text{features}}`. .....scikit-learn.org/stable/_sources/modules/linear_model.rst.txt -
2.3. Clustering — scikit-learn 1.7.2 documentation
\[\text{ARI} = \frac{\text{RI} - E[\text{RI}]}{\max(\text{RI})...index: \[\text{AMI} = \frac{\text{MI} - E[\text{MI}]}{\text{mean}(H(U),...scikit-learn.org/stable/modules/clustering.html -
f1_score — scikit-learn 1.7.2 documentation
\[\text{F1} = \frac{2 * \text{TP}}{2 * \text{TP} + \text{FP}...\text{FP} + \text{FN}}\] Where \(\text{TP}\) is the number of true positives,...scikit-learn.org/stable/modules/generated/sklearn.metrics.f1_score.html