Question 5What type of explanation method can be used to explain different types of Machine Learning models no matter the model structures and complexity?1 pointModel Trust ExplanationsModel-Agnostic ExplanationsLocal Interpretable Model-Agnostic Explanations (LIME)Model Explanations

Question 4What can help humans to interpret the behaviors and methods of Machine Learning models more easily?1 pointModel TrustModel ExplanationsModel DebugExplanation Debug

Explain various machine learning models with examples.

Explain classification model in machine learning with examples .

Say you are building an AI system to help make diagnoses from X-ray scans. Which of the following statements about explainability of AI do you agree with?1 pointLack of explainability can hamper users’ willingness to trust and adopt an AI system.Explainability is usually achieved through building a chatbot to talk to the user to explain its outputs.Most AI systems are highly explainable, meaning that it’s easy for a doctor to figure out why an AI system gave a particular diagnosis.AI systems are intrinsically “black box” and cannot give any explanation for their outputs.

Which of the following is not a common way to get interpretable insights from a model?Group of answer choicesUse feature importance plots to understand which features are contributing value to the model.Use a precision-recall curve to show classifier performance at different thresholds.Use an instance based explanation method such as LIME or SHAP.Use Partial Dependency Plots to show how an individual feature influences model decisions, holding all else constant.