virhekäyriä
Virhekäyriä, meaning "error curves" in Finnish, refers to visualizations used in various fields, particularly in machine learning and statistics, to represent the performance of a model or algorithm. These curves typically plot a performance metric against a varying parameter or threshold. The most common types of error curves include ROC curves and precision-recall curves.
A Receiver Operating Characteristic (ROC) curve plots the true positive rate (sensitivity) against the false positive
Precision-recall curves, on the other hand, plot precision (the proportion of true positive predictions among all
The interpretation of error curves allows for informed decisions regarding model selection, hyperparameter tuning, and threshold