Confusion Matrix
A table showing true positives, true negatives, false positives, and false negatives for classification evaluation.
Related Concepts
- Precision: Explore how Precision relates to Confusion Matrix
- Recall: Explore how Recall relates to Confusion Matrix
- Accuracy: Explore how Accuracy relates to Confusion Matrix
- Classification: Explore how Classification relates to Confusion Matrix
Why It Matters
Understanding Confusion Matrix is crucial for anyone working with model evaluation. This concept helps build a foundation for more advanced topics in AI and machine learning.
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This term is part of the comprehensive AI/ML glossary. Explore related terms to deepen your understanding of this interconnected field.
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Related Terms
Accuracy
The proportion of correct predictions out of total predictions, a basic classification metric.
Classification
A supervised learning task where the model predicts discrete class labels (categories) for input data.
Precision
The proportion of true positives among all positive predictions - measures how many predicted positives are actually positive.
Recall
The proportion of true positives among all actual positives - measures how many actual positives were correctly identified.