Microsoft
DP-100 · Question #149
You have a comma-separated values (CSV) file containing data from which you want to train a classification model. You are using the Automated Machine Learning interface in Azure Machine Learning…
The correct answer is C. Clear the option to perform automatic featurization. Automatic featurization can fit non-linear models. https://econml.azurewebsites.net/spec/estimation/dml.html https://docs.microsoft.com/en-us/azure/machine-learning/how-to-use-automated-ml-for-ml-
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Question
You have a comma-separated values (CSV) file containing data from which you want to train a classification model. You are using the Automated Machine Learning interface in Azure Machine Learning studio to train the classification model. You set the task type to Classification. You need to ensure that the Automated Machine Learning process evaluates only linear models. What should you do?
Options
- AAdd all algorithms other than linear ones to the blocked algorithms list.
- BSet the Exit criterion option to a metric score threshold.
- CClear the option to perform automatic featurization.
- DClear the option to enable deep learning.
- ESet the task type to Regression.
How the community answered
(35 responses)- A3% (1)
- B3% (1)
- C71% (25)
- D9% (3)
- E14% (5)
Explanation
Automatic featurization can fit non-linear models. https://econml.azurewebsites.net/spec/estimation/dml.html https://docs.microsoft.com/en-us/azure/machine-learning/how-to-use-automated-ml-for-ml-
Topics
#Automated Machine Learning (AutoML)#Featurization#Classification Models#Model Constraint
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