Precision and recall - Wikipedia
RDKit blog - A Ternary GHOST
Balanced Accuracy: When Should You Use It?
MVPA Meanderings: balanced accuracy: what and why?
Evaluation of binary classifiers - Wikipedia
Remote Sensing | Free Full-Text | Trends in Remote Sensing Accuracy Assessment Approaches in the Context of Natural Resources
Cohen's Kappa: What It Is, When to Use It, and How to Avoid Its Pitfalls - The New Stack
The Matthews correlation coefficient (MCC) is more reliable than balanced accuracy, bookmaker informedness, and markedness in two-class confusion matrix evaluation | BioData Mining | Full Text
RDKit blog - A Ternary GHOST
Per-continent, box plots of the performance metrics (Balanced Accuracy... | Download Scientific Diagram
Balanced Accuracy: When Should You Use It?
Comparison of model metrics (balanced accuracy and kappa, left and... | Download Scientific Diagram
Remote Sensing | Free Full-Text | An Exploration of Some Pitfalls of Thematic Map Assessment Using the New Map Tools Resource
6 More Evaluation Metrics Data Scientists Should Be Familiar with — Lessons from A High-rank Kagglers' New Book | by Moto DEI | Towards Data Science
The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation | BMC Genomics | Full Text
Sensors | Free Full-Text | QADI as a New Method and Alternative to Kappa for Accuracy Assessment of Remote Sensing-Based Image Classification
Balanced accuracy and F1 score – way to be a data scientist
regression - How to calculate information included in R's confusion matrix - Cross Validated
Cohen's Kappa: What it is, when to use it, and how to avoid its pitfalls | by Rosaria Silipo | Towards Data Science
Cohen's Kappa: What It Is, When to Use It, and How to Avoid Its Pitfalls - The New Stack
17 Measuring Performance | The caret Package
