How to Build an Explainable AI Analysis Pipeline Using SHAP-IQ to Understand Feature Importance, Interaction Effects, and Model Decision Breakdown
INSTANCE_I = int(np.clip(INSTANCE_I, 0, len(X_test)-1)) x = X_test.iloc.values y_true = float(y_test.iloc) pred = float(model.predict()) iv = explainer.explain(x, budget=int(BUDGET_LOCAL), random_state=0) baseline...
