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NEW QUESTION: 1
ノーザントレイルアウトフィッターズにはいくつかのビジネスユニット（BU）があり、各BUは製品情報などの特定のデータ拡張機能を使用します。
これらのデータソースをどのように構成する必要がありますか？
A. ファイル転送アクティビティを使用して、各BUにデータをインポートします。
B. 各BUに製品データのローカルコピーを作成します。
C. すべてのデータを表示できるように、ユーザーに管理者ロールを付与します。
D. トップレベルのBUからのデータ拡張を共有します。
Answer: C
NEW QUESTION: 2
次のうちどれがチーム開発段階の順序を表していますか？
A. フォーミング、パフォーマンス、ストーム、ノーミング
B. フォーミング、ノーミング、ストーム、パフォーマンス
C. フォーミング、ストーム、ノーミング、パフォーマンス
D. フォーミング、ノーミング、パフォーマンス、ストーム
Answer: C
NEW QUESTION: 3
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?
A. Clear the option to enable deep learning.
B. Add all algorithms other than linear ones to the blocked algorithms list.
C. Set the task type to Regression
D. Clear the option to perform automatic featurization.
E. Set the Exit criterion option to a metric score threshold.
Answer: D
Explanation:
Explanation
Automatic featurization can fit non-linear models.
Reference:
https://econml.azurewebsites.net/spec/estimation/dml.html
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-use-automated-ml-for-ml-models