Comparing different models

We have run the experiments in this section for each of the models covered and verified all the different artifacts. Just by looking at our baseline experiment table, and by selecting the common custom metric, f1_experiment_score, we can see that the best performing model is the logistic regression-based model, with an F-score of 0.66:

Figure 4.10 – Comparing different model performance in terms of the goal metric

Metrics can also be compared side by side, as shown in the excerpt in Figure 4.11. On the left side, we have the SKlearn model, and on the right the XGBoost model, with the custom metrics of f1_experiment_score. We can see that the metrics provided by both are different and, hence, the reason for custom metrics when we have different models:

Figure 4.11 – Metrics of the Sklearn model

After comparing the metrics, it becomes clear that the best model is logistic regression. To improve...