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When should you use a confusion matrix?
When you want to create a decision tree
When you want to determine the value you should use as a threshold for your
model
When you want to see if predictions made using logistic regression match
actual outcomes
When you want to automate a process



Answer :

GinnyAnswer

Final answer:

A confusion matrix is utilized in machine learning to evaluate model performance by comparing predicted values with actual values, assessing metrics like sensitivity, specificity, and accuracy.


Explanation:

A confusion matrix is used in machine learning to evaluate the performance of a classification model by comparing predicted values with actual values. It is especially useful in assessing metrics like sensitivity, specificity, and accuracy.


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