What is a confusion matrix?
An example of an AI chatbot conversation about understanding confusion matrices in machine learning.
What is a confusion matrix?
A confusion matrix is a table used to evaluate the performance of a classification model. It shows the true vs. predicted classifications.
Can you explain the components of a confusion matrix?
Sure! A confusion matrix typically includes True Positives, True Negatives, False Positives, and False Negatives.
How do I calculate accuracy from a confusion matrix?
Accuracy is calculated as (True Positives + True Negatives) / Total Predictions. It gives you the proportion of correct predictions.
What are some limitations of using a confusion matrix?
One limitation is that it doesn't provide insights into the types of errors made, and it can be misleading with imbalanced datasets.
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