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NEW QUESTION: 1
You build a machine learning model by using the automated machine learning user interface (UI).
You need to ensure that the model meets the Microsoft transparency principle for responsible AI.
What should you do?
A. Set Validation type to Auto.
B. Set Primary metric to accuracy.
C. Enable Explain best model.
D. Set Max concurrent iterations to 0.
Answer: C
Explanation:
Explanation
Model Explain Ability.
Most businesses run on trust and being able to open the ML "black box" helps build transparency and trust. In heavily regulated industries like healthcare and banking, it is critical to comply with regulations and best practices. One key aspect of this is understanding the relationship between input variables (features) and model output. Knowing both the magnitude and direction of the impact each feature (feature importance) has on the predicted value helps better understand and explain the model. With model explain ability, we enable you to understand feature importance as part of automated ML runs.
Reference:
https://azure.microsoft.com/en-us/blog/new-automated-machine-learning-capabilities-in-azure-machine-learning
NEW QUESTION: 2
The first two steps in the data science process are:
A. Acquire & Ingest Data source(s)
B. Choose Data Sources
C. Develop Data Science Hypotheses and Mehods
D. Define Big Data data strategy & Business Need(s)
Answer: B,D
NEW QUESTION: 3
Drag and drop the functionalities from the left onto the correct target fields on the right.
Answer:
Explanation: