Issue 65

V. Le-Ngoc et alii, Frattura ed Integrità Strutturale, 65 (2023) 300-319; DOI: 10.3221/IGF-ESIS.65.20

 Recall (also known as sensitivity): This metric indicates how well a classifier can predict a correct classification. It is calculated as follows: TP recall= (TP+FN) (18)  Precision: Precision is another important performance metric used to evaluate the performance of a classification model. Precision focuses on the proportion of correct positive predictions. It is calculated as:

TP

precision=

(19)

(TP+FP)

Figure 14: Decision tree model.

Figure 15: The performance of classification models.

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