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NEW QUESTION: 1
データのクレンジングと整形に使用されるサービスはどれですか?
A. データシェイパー
B. データ精製所
C. ワトソンナレッジスタジオ
D. データクレンザー
Answer: B
Explanation:
https://www.ibm.com/support/producthub/icpdata/docs/content/SSQNUZ_current/wsj/refinery/refining_data.html

NEW QUESTION: 2
クラスタコンピューティングアプリケーションには、可能な限り最高のネットワークパフォーマンスが必要です。
10ギガビット拡張ネットワーキングをサポートする同種のインスタンスタイプをすでに選択し、ワークロードがネットワークにバインドされていることを確認し、インスタンスを配置グループに配置しました。
あなたが作ることができる最後の最適化は何ですか?
A. TCPスタックでSYN / ACKをオフにするか、より高いスループットのためにUDPの使用を開始します。
B. すべてを配置グループに維持しながら、インスタンスをピアリングされた異なるVPCに分離し、各インスタンスが独自のインターネットゲートウェイを持つようにします。
C. インスタンスのAMIをベイクして再起動します。これにより、インスタンスはプレースメントグループで新鮮になり、ノイズの多いネイバーがなくなります。
D. ジャンボフレームに1500ではなく9001 MTUを使用して、パケットボディとパケットオーバーヘッドの比率を上げます。
Answer: D
Explanation:
For instances that are collocated inside a placement group, jumbo frames help to achieve the maximum network throughput possible, and they are recommended in this case.
For more information, see Placement Groups.
http://docs.aws.amazon.com/AWSEC2/latest/UserGuide/network_mtu.html#jumbo_frame_instanc es

NEW QUESTION: 3
Azure Machine Learning Studioで分類タスクを実行しています。
提供されたデータセットに基づいて、バランスの取れたテストおよびトレーニングサンプルを準備する必要があります。
0.75:0.25の比率でデータを分割する必要があります。
各パラメーターにどの値を使用する必要がありますか? 回答するには、回答エリアで適切なオプションを選択します。
注:それぞれの正しい選択には1ポイントの価値があります。

Answer:
Explanation:

Explanation

Box 1: Split rows
Use the Split Rows option if you just want to divide the data into two parts. You can specify the percentage of data to put in each split, but by default, the data is divided 50-50.
You can also randomize the selection of rows in each group, and use stratified sampling. In stratified sampling, you must select a single column of data for which you want values to be apportioned equally among the two result datasets.
Box 2: 0.75
If you specify a number as a percentage, or if you use a string that contains the "%" character, the value is interpreted as a percentage. All percentage values must be within the range (0, 100), not including the values 0 and 100.
Box 3: Yes
To ensure splits are balanced.
Box 4: No
If you use the option for a stratified split, the output datasets can be further divided by subgroups, by selecting a strata column.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/split-data

NEW QUESTION: 4
SAP S / 4HANAでどのタイプの製品タイプを使用できますか?
A. 類似の支出項目をグループ化できるようにするため
B. 品目コードを内部または外部に割り当てることができるかどうかを定義します。
C. 類似した材料のグループ化を可能にする
D. 品目タイプが品目かサービスかを定義します
Answer: D