What is the Confusion Matrix, and what information does it provide about a classification model?
- A matrix representing classification errors
- A matrix representing feature importance
- A matrix representing model's coefficients
- A matrix representing model's hyperparameters
The Confusion Matrix is a table that describes the performance of a classification model by categorizing predictions into True Positives, False Positives, True Negatives, and False Negatives. It gives detailed insight into where the model is making mistakes.
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