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getting_started.rst.txt
X_test, y_train, y_test = train_test_split(X, y, random_state=0)...>>> X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)...scikit-learn.org/stable/_sources/getting_started.rst.txt -
QuadraticDiscriminantAnalysis — scikit-learn 1....
n_features) Array of samples (test vectors). Returns : C ndarray...classification on an array of test vectors X. The predicted class...scikit-learn.org/stable/modules/generated/sklearn.discriminant_analysis.QuadraticDiscriminantAnal... -
RAG vs. Fine Tuning, a practical approach - Ela...
search Chatbot test case: Pear Store We will use a test case based...follows: RAG vs Fine Tuning Chatbot test case: Pear Store Approach 1:...www.elastic.co/search-labs/blog/rag-vs-fine-tuning -
Model Selection — scikit-learn 1.6.1 documentation
(ROC) Nested versus non-nested cross-validation Nested versus...regularization on training and test error Effect of model regularization...scikit-learn.org/stable/auto_examples/model_selection/index.html -
StratifiedGroupKFold — scikit-learn 1.6.1 docum...
print ( f " Test: index= { test_index } " ) ... print...indices for that split. test ndarray The testing set indices for that...scikit-learn.org/stable/modules/generated/sklearn.model_selection.StratifiedGroupKFold.html -
DummyClassifier — scikit-learn 1.6.1 documentation
n_features) Test samples. Passing None as test samples gives...# Perform classification on test vectors X. Parameters : X array-like...scikit-learn.org/stable/modules/generated/sklearn.dummy.DummyClassifier.html -
NearestCentroid — scikit-learn 1.6.1 documentation
with test samples classified to the class...n_features) Array of samples (test vectors). Returns : y_scores...scikit-learn.org/stable/modules/generated/sklearn.neighbors.NearestCentroid.html -
MultinomialNB — scikit-learn 1.6.1 documentation
classification of text documents Out-of-core classification of text documents...classification on an array of test vectors X. Parameters : X array-like...scikit-learn.org/stable/modules/generated/sklearn.naive_bayes.MultinomialNB.html -
plot_classifier_comparison.zip
and test part X, y = ds X_train, X_test, y_train, y_test = train_test_split(...Plot the testing points ax.scatter( X_test[:, 0], X_test[:, 1],...scikit-learn.org/stable/_downloads/ce35bcc69acbd491cf7ac77fa17889d5/plot_classifier_comparison.zip -
plot_multi_metric_evaluation.py
1)[0][0] best_score = results["mean_test_%s" % scorer][best_index]...etc...) The ``best_estimator_``, ``best_index_``, ``best_score_``...scikit-learn.org/stable/_downloads/dedbcc9464f3269f4f012f4bfc7d16da/plot_multi_metric_evaluation.py