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NEW QUESTION: 1
The door magnetic sensor has the function of monitoring the opening and closing information of the door, and has the same position in the APM30H/RFC/TM11H, IBBS200D/IBBS200T, IBBS300D/IBBS300T, and IBBS20D cabinets.
A. False
B. True
Answer: B

NEW QUESTION: 2
Which of the possible Simplified Routing modes should be used when installing the SteelHead on an 802.1Q trunk? (Choose three.)
A. Destination and Source
B. All
C. Destination Only
D. None
Answer: A,B,C
Explanation:
In All mode the SteelHead collects mappings for destination and source IP, destination and source MAC, VLAN tag, and Steelhead appliance inner connection traffic and auto-discovery options. This option has the advantage of learning simplified entries faster than the destination only. option Riverbed recommends that you use <all> in topologies when you deploy the Steelhead appliance a 802.1q trunk.
In Destination and source mode the SteelHead collects mappings from destination and source IP, destination and source MAC, and VLAN tag (when deployed on 802.1q trunk).
In Destination only mode the SteelHead collects mappings from destination IP, destination MAC, and VLAN tag (when deployed on 802.1q trunk).
References:SteelheadAppliance Deployment Guide, Including the Steelhead Mobile Controller, December
2013, page 194

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。
run.log_table（ 'ラベル値'、label_vals）
ソリューションは目標を達成していますか？
A. はい
B. いいえ
Answer: B
Explanation:
Explanation
Instead use the run_log function 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