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LinearDiscriminantAnalysis — scikit-learn 1.5.2...
n_features) Array of samples (test vectors). Returns : C ndarray...the mean accuracy on the given test data and labels. In multi-label...scikit-learn.org/stable/modules/generated/sklearn.discriminant_analysis.LinearDiscriminantAnalysi... -
DBFluteのリポジトリ (Github) | DBFlute
(サンプル) DBFlute Test DBFluteのテストプロジェクト。 DBFlute Test https://git...Project DBFlute Example DBFlute Test UTFlute EMecha DBFlute Session...dbflute.seasar.org/ja/environment/repository.html -
Trained models | Machine Learning in the Elasti...
learning model that is trained and tested against a labeled data set....default settings. (Optional) Test your pipeline by running a simulation...www.elastic.co/guide/en/machine-learning/current/ml-trained-models.html -
Chinese Spies Spent Months Inside Aerospace Eng...
competent exposure test (not even a full pen-test), which you can...yro.slashdot.org/story/24/09/18/2014240/chinese-spies-spent-months-inside-aerospace-engineering-f... -
Elastic contributes its Universal Profiling age...
development phase or under controlled test conditions, continuous profiling...During this phase, users can test early preview versions of the...www.elastic.co/observability-labs/blog/elastic-profiling-agent-acceptance-opentelemetry -
set_config — scikit-learn 1.5.2 documentation
for easier benchmarking and testing of scikit-learn internals....for easier benchmarking and testing of scikit-learn internals....scikit-learn.org/stable/modules/generated/sklearn.set_config.html -
1.17. Neural network models (supervised) — scik...
transformation to test data >>> X_test = scaler . transform ( X_test ) An...apply the same scaling to the test set for meaningful results....scikit-learn.org/stable/modules/neural_networks_supervised.html -
LarsCV — scikit-learn 1.5.2 documentation
test) splits as arrays of indices....shape (n_samples, n_features) Test samples. For some estimators...scikit-learn.org/stable/modules/generated/sklearn.linear_model.LarsCV.html -
MLPClassifier — scikit-learn 1.5.2 documentation
X_test , y_train , y_test = train_test_split ( X ,...1]) >>> clf . score ( X_test , y_test ) 0.8... fit ( X , y ) [source]...scikit-learn.org/stable/modules/generated/sklearn.neural_network.MLPClassifier.html -
Team list
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