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→Пример использования (через scikit-learn)
'''from''' sklearn.model_selection '''import''' train_test_split
X_train, X_validationX_test, y_train, y_validation y_test = train_test_split(X, y, test_size=0.2, random_state=1234)
* Создаем классификатор
best_model = KNeighborsClassifier(**best_params)
best_model.fit(X_train, y_train)
predicted = best_model.predict(X_validationX_test)
* Выводим результат
print('Used params:', best_params)
print('Evaluation:\n', metrics.classification_report(y_validationy_test, predicted))
> '''Used params''': {'metric_params': None, 'metric': 'euclidean', 'weights': 'distance', 'n_neighbors': 9, 'leaf_size': 30, 'n_jobs': 4, 'p': 2, 'algorithm': 'auto'}
