Consciousness in AI
Machine Learning
A table showing correct and incorrect predictions for each class, allowing detailed analysis of model performance.
Detailed Explanation
A confusion matrix is a table used in machine learning classification tasks to evaluate the performance of a model. It displays the counts of true positives, true negatives, false positives, and false negatives for each class. This detailed breakdown helps identify where the model makes errors and guides improvements in accuracy, precision, recall, and overall effectiveness.
Use Cases
- •Use case: Evaluate a spam classifier’s accuracy and identify common misclassifications to improve email filtering performance.
Related Terms
Other terms in the Machine Learning category