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Supervised Learning: Difference between revisions
→Metrics
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==Metrics== | ==Metrics== | ||
===Precision and Recall=== | ===Precision and Recall=== | ||
[https://developers.google.com/machine-learning/crash-course/classification/precision-and-recall Google ML Crash Course Precision and Recall] | |||
Precision is (# correct) / (# predictions) or (true positive) / (true positive + false positive). | Precision is (# correct) / (# predictions) or (true positive) / (true positive + false positive). | ||
Recall is (# correct) / (# ground truth) or (true positive) / (true positive + false negative). | Recall is (# correct) / (# ground truth) or (true positive) / (true positive + false negative). | ||
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====ROC Curve==== | ====ROC Curve==== | ||
[https://developers.google.com/machine-learning/crash-course/classification/roc-and-auc Google ML Crash Course ROC and AUC] | |||
True Positive Rate (TPR) = (true positive) / (true positive + false negative). | |||
False Positive Rate (FPR) = (false positive) / (false positive + true negative). | |||
An ROC curve plots TPR vs FPR. | |||