Performance metrics

After a successful solution is found, it is crucial to compare it with other solutions to estimate how good it is. There are many important statistical metrics that compare different models.

Become familiar with concepts such as precision score, recall score, F1 score, ROC AUC, and accuracy. Understanding these metrics will help you to compare the results produced by different models in various classification tasks. Next, we give a brief overview of these metrics.

Precision score

The precision score attempts to answer the question of how many among the positive identifications are actually correct. The precision score can be calculated as follows:

TP is the true positives, and FP is the false positives...