What are the three primary outputs of the model fitting process described in the chapter?

The three primary outputs of the model fitting process are the classification report, the confusion matrix plot, and the feature importance plot.

During the model fitting process, the model generates several outputs that are crucial for evaluating its performance. The classification report provides metrics such as precision, recall, F1 score, and accuracy. The confusion matrix plot visually represents the model's predictions against the actual values, allowing for a quick assessment of prediction accuracy. Additionally, the feature importance plot indicates how much each feature contributes to the model's predictions, helping to identify which variables are most influential.