שאלה | You trained a binary classifier and obtained the following confusion matrix: Predicted Positive Predicted Negative Actual Positive 80 20 Actual Negative 120 780 Which of the following statements is most accurate based on the confusion matrix? (סידור נכון: TP = 80 , TN=780 , FP=120 תFN=20 ) (מועד א 2025 סמסטר ב)

You trained a binary classifier and obtained the following confusion matrix: Predicted Positive Predicted Negative Actual Positive 80 20 Actual Negative 120 780 Which of the following statements is most accurate based on the confusion matrix? (סידור נכון: TP = 80 , TN=780 , FP=120 תFN=20 ) (מועד א 2025 סמסטר ב)

		The model’s high true negative count indicates strong performance, but it may still be unreliable for identifying actual positives
		The model has balanced precision and recall, making it ideal for all classification problems
		The model has high specificity but low sensitivity, making it suitable when false negatives are acceptable
		The model has high recall but low precision, making it suitable for use cases where catching positives is critical despite many false alarms

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