Displays a summary of feature importance and their effects on model predictions.
Provides a comprehensive overview of how each feature contributes to individual predictions and the overall model behavior.
Visualizes the impact of each feature on an individual prediction.
Shows how the contributions of each feature lead to the final predicted outcome for a specific instance.
Illustrates the relationship between a single feature and the predicted outcome.
Helps understand how changing the value of a feature influences the model's predictions while considering the effects of other features.
Displays the interactions between pairs of features and their effects on model predictions.
Provides insights into how the combined effects of two features influence the model's predictions, highlighting synergistic or antagonistic relationships.
Visualizes the decision process of a complex model for a specific prediction.
Shows the sequence of feature contributions that lead to the final predicted outcome, helping understand the decision-making process of the model.
Illustrates the breakdown of a prediction into individual feature contributions.
Provides a step-by-step explanation of how each feature contributes to the final predicted outcome, enhancing transparency and interpretability.
Summarizes the interactions between pairs of features across multiple predictions.
Helps identify global patterns of feature interactions and their effects on model predictions, providing insights into the model's behavior.
Combines the summary plot and dependence plot to visualize the relationship between feature importance and their effects on predictions.
Provides a holistic view of how each feature contributes to model predictions while considering their individual and collective impacts.
Visualizes the decision paths of tree-based models and their effects on model predictions.
Shows how different features are split at each node of the decision tree, helping understand the logic behind the model's predictions.