What are the components of a Confusion Matrix, and how do they relate to the True Positive, False Positive, True Negative, and False Negative rates?
- TP, FN, FP, TN, associated with model accuracy
- TP, FP, FN, TN, associated with specific classes
- TP, FP, TN, FN, associated with different error types
- nan
A Confusion Matrix consists of True Positives (TP), False Positives (FP), True Negatives (TN), and False Negatives (FN). They help in understanding the type of mistakes a classifier is making, providing insight into the model's ability to classify instances of specific classes.
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