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# تدريب النموذج على بيانات التدريب | |
LR_clf = LogisticRegression().fit(X_train, y_train) | |
# اختبار النموذج عن طريق توقع بيانات الاختبار | |
LR_prediction = LR_clf.predict(X_test) | |
# التحقق من ضبط النموذج عن طريق مقارنة القيم الحقيقية و القيم المتوقعة | |
LR_accuracy = accuracy_score(y_test, prediction)*100 | |
# Accuracy | الضبط | |
print(f'Logistic Regression Classifier accuracy: {LR_accuracy:.2f} %') |
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