Sensitivity Analysis for Model Interpretability

Advanced

Understand how model predictions change with input perturbations. Master finite difference methods, gradient estimation, Sobol indices, and local sensitivity analysis for model interpretability.

75 min Lab: notebook 5 objectives 4 evidence types
Open Interactive Lab
75
Minutes
5
Objectives
4
Evidence Types
4
Success Criteria

Case Narrative

Learning Objectives

1
Understand local vs global sensitivity analysis
2
Apply finite difference methods for gradient approximation
3
Compute Sobol indices for global feature importance
4
Assess model robustness to input perturbations
5
Integrate sensitivity analysis into model development workflows

Required Evidence

Gradient Estimation Not collected yet
Sobol Computation Not collected yet
Robustness Assessment Not collected yet
Feature Ranking Not collected yet

Case Details

Difficulty
Advanced
Duration
75 min
Lab Type
notebook
Slug
sensitivity-analysis

Prerequisites

No prerequisites - open to all

Success Criteria

Feature Ranking Produced Required
Finite Differences Applied Required
Robustness Analyzed Required
Sobol Indices Computed Required

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