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NEW QUESTION: 1
Simulating G/L view (Choose Three)
A. allows simulation of entry view as well as G/L view before posting
B. expert mode gives a view of detailed data of document splitting
C. facilitates analysis of an error early that would lead to a termination
D. allows simulation of entry view as well as G/L view after posting
Answer: A,B,C

NEW QUESTION: 2
Which of the following deployment modes is not included in standard NAC?
A. L2 based NAC
B. L3 based NAC
C. System Health based NAC
D. DHCP based NAC
Answer: D

NEW QUESTION: 3
注：この質問は、同じシナリオを提示する一連の質問の一部です。シリーズの各質問には、述べられた目標を達成する可能性のある独自の解決策が含まれています。一部の質問セットには複数の正しい解決策がある場合がありますが、他の質問セットには正しい解決策がない場合があります。
このセクションの質問に回答した後は、その質問に戻ることはできません。その結果、これらの質問はレビュー画面に表示されません。
Pythonスクリプトを使用して、Azure MachineLearningの実験を実行することを計画しています。スクリプトは、実験実行コンテキストへの参照を作成し、ファイルからデータをロードし、ラベル列の一意の値のセットを識別して、実験実行を完了します。
azureml.coreからインポート実行
パンダをpdとしてインポートする
run = Run.get_context（）
データ= pd.read_csv（ 'data.csv'）
label_vals = data ['label']。unique（）
＃ここに指標を記録するコードを追加
run.complete（）
実験では、後で確認できる実行のメトリックとして、データ内の一意のラベルを記録する必要があります。
コメントで示されたポイントで実行メトリックとして一意のラベル値を記録するには、スクリプトにコードを追加する必要があります。
解決策：コメントを次のコードに置き換えます。
label_valsのlabel_valの場合：
run.log（ 'ラベル値'、label_val）
ソリューションは目標を達成していますか？
A. いいえ
B. はい
Answer: B
Explanation:
Explanation
The run_log function is used to log the contents in label_vals:
for label_val in label_vals:
run.log('Label Values', label_val)
Reference:
https://www.element61.be/en/resource/azure-machine-learning-services-complete-toolbox-ai