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NEW QUESTION: 1
You train a classification model by using a decision tree algorithm.
You create an estimator by running the following Python code. The variable feature_names is a list of all feature names, and class_names is a list of all class names.
from interpret.ext.blackbox import TabularExplainer
You need to explain the predictions made by the model for all classes by determining the importance of all features.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: Yes
TabularExplainer calls one of the three SHAP explainers underneath (TreeExplainer, DeepExplainer, or KernelExplainer).
Box 2: Yes
To make your explanations and visualizations more informative, you can choose to pass in feature names and output class names if doing classification.
Box 3: No
TabularExplainer automatically selects the most appropriate one for your use case, but you can call each of its three underlying explainers underneath (TreeExplainer, DeepExplainer, or KernelExplainer) directly.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-machine-learning-interpretability-aml
NEW QUESTION: 2
You need to provide a customer an action plan to update an ONTAP system after a security bulletin has been issued.
In this scenario, how do you accomplish this task?
A. Use the Interoperability Matrix Tool.
B. Review the ONTAP 9 product page.
C. Use Upgrade Advisor on Active IQ.
D. Download the target version and do a pre-check.
Answer: D
NEW QUESTION: 3
행정부가 대학 캠퍼스의 새로운 강도 및 컨디셔닝 시설을 계획하고 타당성 조사를 시작하면 새로운 시설 설계 단계가 진행될 것입니다.
A. 건설
B. 프리 디자인
C. 수술 전
D. 디자인
Answer: B
NEW QUESTION: 4
A. Business analysis
B. Behavior analysis
C. Availability analysis
D. Trend analysis
Answer: D