What are false negatives in machine learning?
An example of an AI chatbot conversation about false negatives in machine learning.
What are false negatives in machine learning?
False negatives occur when a model incorrectly predicts a negative outcome for a positive instance.
Can you give me an example of false negatives?
Sure! In a medical test, a false negative would mean a test fails to detect a disease that is actually present.
Why are false negatives a problem?
They can lead to missed opportunities for treatment, causing harm to patients or incorrect conclusions in research.
How can we reduce false negatives in models?
We can improve data quality, adjust thresholds, and use ensemble methods to enhance model performance.
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