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Question 54 - DP-100 discussion

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DRAG DROP

You have several machine learning models registered in an Azure Machine Learning workspace.

You must use the Fairlearn dashboard to assess fairness in a selected model.

Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.


Question 54
Correct answer: Question 54

Explanation:

Step 1: Select a model feature to be evaluated.

Step 2: Select a binary classification or regression model.

Register your models within Azure Machine Learning. For convenience, store the results in a dictionary, which maps the id of the registered model (a string in name:version format) to the predictor itself.

Example:

model_dict = {}

lr_reg_id = register_model("fairness_logistic_regression", lr_predictor)

model_dict[lr_reg_id] = lr_predictor

svm_reg_id = register_model("fairness_svm", svm_predictor)

model_dict[svm_reg_id] = svm_predictor

Step 3: Select a metric to be measured

Precompute fairness metrics.

Create a dashboard dictionary using Fairlearn's metrics package.

Reference:

https://docs.microsoft.com/en-us/azure/machine-learning/how-to-machine-learning-fairness-aml

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asked 02/10/2024
jateen chibabhai
41 questions
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