Evaluation metrics

In this section, we will take a look at a few metrics that will allow us to mathematically quantify the performance of our classifiers, regressors, and filters.

Accuracy

Accuracy is the most widely used metric to gauge the performance of a classification model. It is the ratio of the number of correct predictions to the total number of predictions made by the model:

Root mean square error

The Root Mean Square Error (or RMSE) is a metric widely used to gauge the performance of regressors...