What aspect do Partial Dependence Plots focus on visualizing?

Partial Dependence Plots (PDPs) specifically aim to visualize the relationship between one or more features and the predicted outcome of a model. By isolating the effect of individual features, PDPs allow insight into how changes in those features influence predictions while averaging out the effects of other features. This makes them a powerful tool for understanding the contributions of specific predictors to the model's output.

When creating a PDP, the value of a particular feature is varied while keeping other features constant, which illustrates the expected prediction as that feature changes. This is crucial for interpreting model behavior, particularly in complex models where direct relationships between input and output may not be immediately apparent.

While other aspects, such as feature interactions and model complexity, are important in the broader context of model interpretation, they are not the primary focus of Partial Dependence Plots, which center on the individual effects of features. Similarly, evaluating overall model performance is distinct from the insights that PDPs provide about feature-specific impacts on predictions.