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Confusion matrix — scikit-learn 1.5.0 documenta...
set and a test set X_train , X_test , y_train , y_test = train_test_split...from_estimator ( classifier , X_test , y_test , display_labels = class_names...scikit-learn.org/stable/auto_examples/model_selection/plot_confusion_matrix.html -
Effect of varying threshold for self-training —...
train_index ] X_test = X [ test_index ] y_test = y [ test_index ] y_test_true...y_test_true = y_true [ test_index ] self_training_clf . fit (...scikit-learn.org/stable/auto_examples/semi_supervised/plot_self_training_varying_threshold.html -
Curve Fitting with Bayesian Ridge Regression — ...
increasing = True ) X_test = np . vander ( x_test , n_order + 1 , increasing...predict ( X_test , return_std = True ) ax . plot ( x_test , func (...scikit-learn.org/stable/auto_examples/linear_model/plot_bayesian_ridge_curvefit.html -
6.3. Preprocessing data — scikit-learn 1.5.0 do...
X_test , y_train , y_test = train_test_split ( X ,...score ( X_test , y_test ) # apply scaling on testing data, without...scikit-learn.org/stable/modules/preprocessing.html -
plot_hgbt_regression.ipynb
import train_test_split\n\nX_train, X_test, y_train, y_test = train_test_split(X,...train_test_split(X, y, test_size=0.4, shuffle=False)\n\nprint(f\"Training...scikit-learn.org/stable/_downloads/cb9a8a373677fb481fe43a11d8fa0e94/plot_hgbt_regression.ipynb -
FixedThresholdClassifier — scikit-learn 1.5.0 d...
X_test , y_train , y_test = train_test_split ( ......confusion_matrix ( y_test , classifier . predict ( X_test ))) [[217 7]...scikit-learn.org/stable/modules/generated/sklearn.model_selection.FixedThresholdClassifier.html -
ShrunkCovariance — scikit-learn 1.5.0 documenta...
: X_test array-like of shape (n_samples, n_features) Test data...the observations. score ( X_test , y = None ) [source] # Compute...scikit-learn.org/stable/modules/generated/sklearn.covariance.ShrunkCovariance.html -
Robust linear estimator fitting — scikit-learn ...
sin ( X_test ) X_test = X_test [:, np . newaxis ] y_errors...newaxis ] X_test = np . random . normal ( size = 200 ) y_test = np ....scikit-learn.org/stable/auto_examples/linear_model/plot_robust_fit.html -
Gaussian processes on discrete data structures ...
) X_test = [ "AAA" , "ATAG" , "CTC" , "CT" , "C" ] Y_test = [...len ( X_test )), [ 1.0 if c else - 1.0 for c in Y_test ], s =...scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpr_on_structured_data.html -
Elastic ServiceNow connector reference | Enterp...
atf_test_designer , atf_test_admin Knowledge admin...sn_request_read , asset , atf_test_designer , atf_test_admin Knowledge admin...www.elastic.co/guide/en/enterprise-search/current/connectors-servicenow.html