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TUTORIAL
environment REST API Building a site using the REST API JSON and...fess.codelibs.org/tutorial.html -
Getting Started
login before they can access the rest of the Administration interface....fess.codelibs.org/getting-started.html -
Part 1: Getting Started with Fess
introduce how to use the full-text search server Fess to implement...Fess is an open source full-text search server that can handle...fess.codelibs.org/articles/1/document.html -
オープンソース全文検索サーバー - ニュース一覧
Fess で作るApache Solrベースの検索サーバー ～ REST API編 」が掲載されました 2010-12-19 Fess...fess.codelibs.org/ja/news.html -
sklearn.model_selection.KFold — scikit-learn 1....
estimates Nested versus non-nested cross-validation Nested versus...Provides train/test indices to split data in train/test sets. Split...scikit-learn.org/stable/modules/generated/sklearn.model_selection.KFold.html -
Synthetic Monitoring with Elastic Observability...
push the test scripts with your code for continued testing in production....code releases and test updates, reuse test scripts to reduce...www.elastic.co/observability/synthetic-monitoring -
sklearn.gaussian_process.GaussianProcessClassif...
{‘one_vs_rest’, ‘one_vs_one’}, default=’one_vs_rest’ Specifies...are ‘one_vs_rest’ and ‘one_vs_one’. In ‘one_vs_rest’, one binary...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.GaussianProcessClassifier.html -
Contributing — scikit-learn 1.4.2 documentation
sklearn/linear_model/tests/test_logistic.py to run the tests specific to...path/to/tests_for_package see also Testing and improving test coverage...scikit-learn.org/stable/developers/contributing.html -
sklearn.discriminant_analysis.QuadraticDiscrimi...
classification on an array of test vectors X. predict_log_proba...the mean accuracy on the given test data and labels. set_params...scikit-learn.org/stable/modules/generated/sklearn.discriminant_analysis.QuadraticDiscriminantAnal... -
Model selection: choosing estimators and their ...
X_digits [ test ], y_digits [ test ]) ... for train , test in k_fold..., y_train ) . score ( X_test , y_test )) >>> print ( scores )...scikit-learn.org/stable/tutorial/statistical_inference/model_selection.html