1 / 14

Performance measures

This document explores various performance measures crucial for evaluating prediction accuracy, including Pearson's correlation coefficient, Matthews correlation coefficient, and ROC curve analysis. Through detailed metrics such as True Positives, False Positives, True Negatives, and False Negatives, we assess the effectiveness of prediction methods. The paper emphasizes the importance of AUC (Area Under the Curve), where values range from 0.5 (random) to 1 (perfect). Key insights into MSE and the relationship between different performance measures are also discussed.

raleigh
Download Presentation

Performance measures

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Performance measures Morten Nielsen

  2. Performance measures MeasPred 0.4050 0.8344 0.9373 1.0000 0.8161 0.6388 0.6752 0.9841 0.0253 0.0000 0.3196 0.5388 0.6764 0.6247 0.1872 0.1921 0.4220 0.6546 0.6545 0.6546 0.7917 0.1342 0.4405 0.3551 0.1548 0.0000 0.2740 0.1993 0.4399 0.6461 0.1725 0.3916 0.0539 0.0000 0.3795 0.5623 0.2242 0.1968 0.3108 0.2114 0.2260 0.0336 0.2780 0.5647 0.0198 0.1224 0.5890 0.5538 0.5120 0.4349 0.7266 1.0000 0.1136 0.0000 0.0456 0.2128 0.0069 0.4100 0.4502 0.3848

  3. Performance measures MeasPred 0.4050 0.8344 0.9373 1.0000 0.8161 0.6388 0.6752 0.9841 0.0253 0.0000 0.3196 0.5388 0.6764 0.6247 0.1872 0.1921 0.4220 0.6546 0.6545 0.6546 0.7917 0.1342 0.4405 0.3551 0.1548 0.0000 0.2740 0.1993 0.4399 0.6461 0.1725 0.3916 0.0539 0.0000 0.3795 0.5623 0.2242 0.1968 0.3108 0.2114 0.2260 0.0336 0.2780 0.5647 0.0198 0.1224 0.5890 0.5538 0.5120 0.4349 0.7266 1.0000 0.1136 0.0000 0.0456 0.2128 0.0069 0.4100 0.4502 0.3848

  4. Pearsons’ correlation coefficient

  5. Performance measures • Accuracy of prediction method Sort

  6. Matthews correlation - Threshold of 0.5

  7. Matthews correlation - Threshold of 0.5

  8. TP FP TN Evaluation of predictionaccuracy FN

  9. AP AN Evaluation of predictionaccuracy

  10. Performance measure – Roccurve 4 10 0.29 1 12 0.08

  11. Performance measure – Roccurve 4 10 0.29 1 12 0.08

  12. ROC curves AUC = 0.5 AUC = 1.0

  13. AUC (area under the ROC curve)

  14. Summary • MSE • Small is good • Perfect = 0.0 • MCC and PCC • Random = 0.0 • Perfect = 1.0 (or -1) • ROC (AUC) • Random = 0.5 • Perfect = 1 (or 0)

More Related