What is threshold adjustment in machine learning?
Threshold adjustment refers to the process of setting a specific cutoff value in classification models to determine the predicted class.
Why is it important to adjust the threshold?
Adjusting the threshold can help balance precision and recall, improving the model's performance based on specific needs.
How do I choose the right threshold for my model?
You can choose the right threshold by analyzing the ROC curve, precision-recall curve, or using cross-validation techniques.
Can threshold adjustment affect model accuracy?
Yes, it can significantly affect accuracy, as it influences the trade-off between false positives and false negatives.
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