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1.9. Naive Bayes — scikit-learn 1.6.1 documenta...
X_test , y_train , y_test = train_test_split ( X ,...: %d " ... % ( X_test . shape [ 0 ], ( y_test != y_pred ) . sum...scikit-learn.org/stable/modules/naive_bayes.html -
Version 0.20 — scikit-learn 1.6.1 documentation
the train and test data are centered with the train...be scored without supplying test samples. #11951 by Rüdiger Busche...scikit-learn.org/stable/whats_new/v0.20.html -
Elastic Serverless | Elastic
Playground - Roll up your sleeves Test the latest AI search capabilities...explore how to build RAG systems, test different LLMs from various...www.elastic.co/demo-gallery/serverless -
is_classifier — scikit-learn 1.6.1 documentation
estimator object Estimator object to test. Returns : out bool True if...scikit-learn.org/stable/modules/generated/sklearn.base.is_classifier.html -
is_clusterer — scikit-learn 1.6.1 documentation
estimator object Estimator object to test. Returns : out bool True if...scikit-learn.org/stable/modules/generated/sklearn.base.is_clusterer.html -
Implementing search and generative AI for your ...
www.elastic.co/resources/search/ebook/implementing-search-for-your-knowledge-base -
gads.js
ads_test"),a)c="preview/"+a;else{var l="test1",p="test2";try...ad_test"in e.ARGV&&"true"==e.ARGV.gooad_test&&(e.GAM_TEST_EN...adcdn.goo.ne.jp/images/js/gads.js -
Observability Tour | Elastic
Playground - Roll up your sleeves Test the latest AI search capabilities...explore how to build RAG systems, test different LLMs from various...www.elastic.co/demo-gallery/observability -
Scaling the regularization parameter for SVCs —...
= 1e-3 ) We compute the mean test score for different values of...train_sizes ] shuffle_params = { "test_size" : 0.3 , "n_splits" : 150...scikit-learn.org/stable/auto_examples/svm/plot_svm_scale_c.html -
MinCovDet — scikit-learn 1.6.1 documentation
: X_test array-like of shape (n_samples, n_features) Test data...Quality, TECHNOMETRICS score ( X_test , y = None ) [source] # Compute...scikit-learn.org/stable/modules/generated/sklearn.covariance.MinCovDet.html