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In Ai and machine learning courses, one of the most important evaluation tools you’ll learn about is the confusion matrix.
A confusion matrix visualizes the performance of a classification model.
It shows:
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True Positives
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True Negatives
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False Positives
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False Negatives
It is extremely useful for calculating accuracy, precision, recall, and F1-score, helping you understand where your model performs well and where it misclassifies data.
Topic starter
Posted : 25/11/2025 5:56 am