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

What can help humans to interpret the behaviors and methods of Machine Learning models more easily?

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

Explain various machine learning models with examples.

Question 3Which of the following is NOT an attribute of Machine Learning? 1 pointTakes data and answers as input and uses these inputs to create a set of rules that determine what the Machine Learning model will be Machine Learning defines behavioral rules by comparing large data sets to find common patternsTakes data and rules as input and uses these inputs to develop an algorithm that will give us an answerMachine Learning models can be continuously trained

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.