ClustEval clustering evaluation framework
The F2-Score is a weighted average of precision and recall: $F_2 = 5 \cdot \frac{precision \cdot recall}{4\cdot precision + recall}$ Where Precision is defined as $\frac{TP}{TP+FP}$ and Recall is defined as $\frac{TP}{TP+FN}$ The F2-Score originates from the binary classification background, where we only have two classes that we want to distinguish: positive and negative. In this scenario there are four possible outcomes: