what is the relative misclassification cost of the model?

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The relative misclassification cost of a model refers to the impact or cost associated with misclassifying instances in the dataset. It signifies the relative importance or consequence of making errors in prediction, such as incorrectly classifying a positive instance as negative (false negative) or a negative instance as positive (false positive). This cost is often used as a parameter in model building to adjust the balance between sensitivity and specificity based on the specific requirements or constraints of the problem at hand.




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