Shobha
The best way to predict the future is to invent it
What is the importance of model interpretability in real-world data analytics applications?
Interpretability ensures that stakeholders can understand how and why a model makes decisions, which is crucial for building trust, especially in industries like healthcare or finance. It also helps in identifying biases and improving the model.For example, Using SHAP values, I can explain how each feature (e.g., age, income) affects the model's prediction, making the model more transparent and understandable.