To visualize the performance of a classification model
To calculate the accuracy of a regression model
To determine feature importance
To optimize hyperparameters
The confusion matrix visualizes the performance of a classification model by showing true positives, false positives, true negatives, and false negatives.
Questions & Step-by-step Solutions
1 item
Q
Q: What is the purpose of the confusion matrix?
Solution: The confusion matrix visualizes the performance of a classification model by showing true positives, false positives, true negatives, and false negatives.
