HOTSPOT -
You need to configure the Permutation Feature Importance module for the model training requirements.
What should you do? To answer, select the appropriate options in the dialog box in the answer area.
NOTE: Each correct selection is worth one point.
Hot Area:
 
















 

Suggested Answer: 
    

Box 1: 500 -
For Random seed, type a value to use as seed for randomization. If you specify 0 (the default), a number is generated based on the system clock.
A seed value is optional, but you should provide a value if you want reproducibility across runs of the same experiment.
Here we must replicate the findings.
Box 2: Mean Absolute Error -
Scenario: Given a trained model and a test dataset, you must compute the Permutation Feature Importance scores of feature variables. You need to set up the
Permutation Feature Importance module to select the correct metric to investigate the model's accuracy and replicate the findings.
Regression. Choose one of the following: Precision, Recall, Mean Absolute Error, Root Mean Squared Error, Relative Absolute Error, Relative Squared Error,
Coefficient of Determination -
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/permutation-feature-importance

This question is in DP-100 Exam
For getting Microsoft Azure Data Scientist Associate Certificate


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